Probability Abstracts 99

This document contains abstracts 5757-5996 from July-1-2007 to August-31-2007.
They have been mailed on September 14th, 2007.

5757. On Bernoulli Decompositions for Random Variables, Concentration Bounds, and Spectral Localization

Author(s): Michael Aizenman and Francois Germinet and Abel Klein and Simone Warzel

Abstract: As was noted already by A. N. Kolmogorov, any random variable has a Bernoulli component. This observation provides a tool for the extension of results which are known for Bernoulli random variables to arbitrary distributions. Two applications are provided here: i. an anti-concentration bound for a class of functions of independent random variables, where probabilistic bounds are extracted from combinatorial results, and ii. a proof, based on the Bernoulli case, of spectral localization for random Schroedinger operators with arbitrary probability distributions for the single site coupling constants. For a general random variable, the Bernoulli component may be defined so that its conditional variance is uniformly positive. The natural maximization problem is an optimal transport question which is also addressed here.

http://arxiv.org/abs/0707.0095

5758. A multi-dimensional Markov chain and the Meixner ensemble

Author(s): Kurt Johansson

Abstract: We show that the transition probability of the Markoc chain $(G(j,1),...,G(j,n))_{j\ge 1}$, where the $G(i,j)'s$ are certain directed last-passage times, is given by a determinant of a special form. An analogous formula has recently been obtained by Warren in a Brownian motion model. Furthermore we demonstrate that this formula leads to the Meixner ensemble when we compute the distribution function for $G(m,n)$. We also obtain the Fredholm determinant representation of this distribution, where the kernel has a double contour integral representation.

http://arxiv.org/abs/0707.0098

5759. Non-degeneracy of Wiener functionals arising from rough differential equations

Author(s): Thomas Cass and Peter Friz and Nicolas Victoir

Abstract: Malliavin Calculus is about Sobolev-type regularity of functionals on Wiener space, the main example being the Ito map obtained by solving stochastic differential equations. Rough path analysis is about strong regularity of solution to (possibly stochastic) differential equations. We combine arguments of both theories and discuss existence of a density for solutions to stochastic differential equations driven by a general class of non-degenerate Gaussian processes, including processes with sample path regularity worse than Brownian motion.

http://arxiv.org/abs/0707.0154

5760. Convex and star-shaped sets associated with stable distributions

Author(s): Ilya Molchanov

Abstract: It is known that each symmetric stable distribution in $R^d$ is related to a norm on $R^d$ that makes $R^d$ embeddable in $L_p([0,1])$. In case of a multivariate Cauchy distribution the unit ball in this norm corresponds is the polar set to a convex set in $R^d$ called a zonoid. This work exploits recent advances in convex geometry in order to come up with new probabilistic results for multivariate stable distributions. In particular, it provides expressions for moments of the Euclidean norm of a stable vector, mixed moments and various integrals of the density function. It is shown how to use geometric inequalities in order to bound important parameters of stable laws. It is shown that each symmetric stable laws appears as the limit for the sum of sub-Gaussian laws and an estimate for the probability distance to a sub-Gaussian law is given. Operations with convex sets induce the well-known and new operations with stable vectors. Furthermore, covariation, regression and orthogonality concepts for stable laws acquire geometric interpretations. A similar collection of results is presented for one-sided stable laws.

http://arxiv.org/abs/0707.0221

5761. LAMN property for hidden processes: the case of integrated diffusions

Author(s): Arnaud Gloter (LAMA) and Emmanuel Gobet (LJK)

Abstract: In this paper we prove the Local Asymptotic Mixed Normality (LAMN) property for the statistical model given by the observation of local means of a diffusion process $X$. Our data are given by $ \int_0^1 X_{\frac{s+i} {n}} \dd \mu (s)$ for $i=0,...,n-1$ and the unknown parameter appears in the diffusion coefficient of the process $X$ only. Although the data are nor Markovian neither Gaussian we can write down, with help of Malliavin calculus, an explicit expression for the log-likelihood of the model, and then study the asymptotic expansion. We actually find that the asymptotic information of this model is the same one as for a usual discrete sampling of $X$.

http://arxiv.org/abs/0707.0257

5762. Maximum Likelihood Estimator for Hidden Markov Models in continuous time

Author(s): Pavel Chigansky

Abstract: The paper studies large sample asymptotic properties of the Maximum Likelihood Estimator (MLE) for the parameter of a continuous time Markov chain, observed in white noise. Using the method of weak convergence of likelihoods due to I.Ibragimov and R.Khasminskii, consistency, asymptotic normality and convergence of moments are established for MLE under certain strong ergodicity conditions of the chain.

http://arxiv.org/abs/0707.0271

5763. A statistical theory for the measurement and estimation of Rayleigh fading channel

Author(s): Xinjia Chen and Guoxiang Gu and Kemin Zhou

Abstract: In this paper, we propose a statistical theory on measurement and estimation of Rayleigh fading channels in wireless communications and provide complete solutions to the fundamental problems: What is the optimum estimator for the statistical parameters associated with the Rayleigh fading channel, and how many measurements are sufficient to estimate these parameters with the prescribed margin of error and confidence level? Our proposed statistical theory suggests that two testing signals of different strength be used. The maximum likelihood (ML) estimator is obtained for estimation of the statistical parameters of the Rayleigh fading channel that is both sufficient and complete statistic. Moreover, the ML estimator is the minimum variance (MV) estimator that in fact achieves the Cramer-Rao lower bound.

http://arxiv.org/abs/0707.0284

5764. Asymptotic Expansion of the One-Loop Approximation of the Chern-Simons Integral in an Abstract Wiener Space Setting

Author(s): Itaru Mitoma and Seiki Nishikawa

Abstract: In an abstract Wiener space setting, we constract a rigorous mathematical model of the one-loop approximation of the perturbative Chern-Simons integral, and derive its explicit asymptotic expansion for stochastic Wilson lines.

http://arxiv.org/abs/0707.0047

5765. On the Optimal Switching Problem for One-Dimensional Diffusions

Author(s): Erhan Bayraktar and Masahiko Egami

Abstract: We characterize the optimal switching problem as coupled optimal stoping problems. We then use the optimal stopping theory to provide a solution. As opposed to the methods using quasi-variational inequalities and verification theorem we directly work with the value function.

http://arxiv.org/abs/0707.0100

5766. Differential Equations Driven by Gaussian Signals I

Author(s): Peter Friz and Nicolas Victoir

Abstract: We consider multi-dimensional Gaussian processes and give a new condition on the covariance, simple and sharp, for the existence of stochastic area (s). Gaussian rough paths are constructed with a variety of weak and strong approximation results. Together with a new RKHS embedding, we obtain a powerful - yet conceptually simple - framework in which to analysize differential equations driven by Gaussian signals in the rough paths sense.

http://arxiv.org/abs/0707.0313

5767. Occupation time fluctuations of Poisson and equilibrium branching systems in critical and large dimensions

Author(s): Piotr Milos

Abstract: Limit theorems are presented for the rescaled occupation time fluctuation process of a critical finite variance branching particle system in $\mathbb{R}^{d}$ with symmetric $\alpha$-stable motion starting off from either a standard Poisson random field or the equilibrium distribution for critical $d=2\alpha$ and large $d>2\alpha$ dimensions. The limit processes are generalised Wiener processes. The obtained convergence is in space-time, finite-dimensional distributions sense. With the addtional assumption on the branching law we obtain functional convergence.

http://arxiv.org/abs/0707.0316

5768. Large deviations for symmetrised empirical measures

Author(s): Jos\'e Trashorras

Abstract: In this paper we prove a Large Deviation Principle for the sequence of symmetrised empirical measures $\frac{1}{n} \sum_{i=1}^{n} \delta_{(X^n_i,X^n_{\sigma_n(i)})}$ where $\sigma_n$ is a random permutation and $((X_i^n)_{1 \leq i \leq n})_{n \geq 1}$ is a triangular array of random variables with suitable properties. As an application we show how this result allows to improve the Large Deviation Principles for symmetrised initial-terminal conditions bridge processes recently established by Adams, Dorlas and K\"{o}nig.

http://arxiv.org/abs/0707.0344

5769. Radial Dunkl Processes : Existence and uniqueness, Hitting time, Beta Processes and Random Matrices

Author(s): Nizar Demni (PMA)

Abstract: We begin with the study of some properties of the radial Dunkl process associated to a reduced root system $R$. It is shown that this diffusion is the unique strong solution for all $t \geq 0$ of a SDE with singular drift. Then, we study $T_0$, the first hitting time of the positive Weyl chamber : we prove, via stochastic calculus, a result already obtained by Chybiryakov on the finiteness of $T_0$. The second and new part deals with the law of $T_0$ for which we compute the tail distribution, as well as some insight via stochastic calculus on how root systems are connected with eigenvalues of standard matrix-valued processes. This gives rise to the so-called $\beta$- processes. The ultraspherical $\beta$-Jacobi case still involves a reduced root system while the general case is closely connected to a non reduced one. This process lives in a convex bounded domain known as principal Weyl alcove and the strong uniqueness result remains valid. The last part deals with the first hitting time of the alcove's boundary and the semi group density which enables us to answer some open questions.

http://arxiv.org/abs/0707.0367

5770. Dyson's non-intersecting Brownian motions with a few outliers

Author(s): Mark Adler and Jonathan Delepine and Pierre van Moerbeke

Abstract: Consider n non-intersecting Brownian particles on the real line (Dyson Brownian motions), all starting from the origin at time t=0, and evolving up to time t=1. Assume that, among those particles, r are forced to reach a given final target a >0 (outliers), while the (n-r) remaining ones return to the position x=0. Letting n tend to infinity, view this cloud of particles from the edge (i.e., near the largest particle), with the space and time rescaling given by the edge statistics of GUE. Also let the target point a go to infinity with n at the rate a=rho\sqrt{n/2} for rho between 0 and 1. Then a phase transition takes place at rho=1. Indeed, for rho<1, the limit cloud is described by the Airy process, which in effect is rho-independent and also independent of the number r of outlying particles; it is as if rho were =0. For rho=1, the process depends on the number r of outliers, and leads to a new process: an Airy process with r outliers (in short: r-Airy process), which is a kind of interpolation between the Airy and Pearcey processes. The log of the probability that at time tau (the new rescaled time) the cloud does not exceed x is given by the Fredholm determinant of a new kernel (extending the Airy kernel) and it satisfies a non-linear PDE in x and tau, from which the asymptotic behavior of the process can be deduced for tau tending to -infinity (remote past). This kernel is closely related to one found by Baik, Ben Arous and Peche in the context of multivariate statistics.

http://arxiv.org/abs/0707.0442

5771. Rubinstein distance on configurations spaces

Author(s): Laurent Decreusefond and Nicolas Savy

Abstract: By a method inspired of the Stein's method, we derive an upper- bound of the Rubinstein distance between two absolutely continuous probability measures on configurations space. As an application, we show that the best way to approximate a Modulated Poisson Process (see below for the definition) by a Poisson process is to equate their intensity.

http://arxiv.org/abs/0707.0445

5772. Stochastic domination for iterated convlutions and catalytic majorization

Author(s): Guillaume Aubrun (ICJ) and Ion Nechita (ICJ)

Abstract: We study how iterated convolutions of probability measures compare under stochastic domination. We give necessary and sufficient conditions for the existence of an integer $n$ such that $\mu^{*n}$ is stochastically dominated by $\nu^{*n}$ for two given probability measures $\mu$ and $\nu$. As a consequence we obtain a similar theorem on the majorization order for vectors in $ \R^d$. In particular we prove results about catalysis in quantum information theory.

http://arxiv.org/abs/0707.0211

5773. Random Normal Matrices and Polynomial Curves

Author(s): Peter Elbau

Abstract: We show that in the large matrix limit, the eigenvalues of the normal matrix model for matrices with spectrum inside a compact domain with a special class of potentials homogeneously fill the interior of a polynomial curve uniquely defined by the area of its interior domain and its exterior harmonic moments which are all given as parameters of the potential. Then we consider the orthogonal polynomials corresponding to this matrix model and show that, under certain assumptions, the density of the zeros of the highest relevant orthogonal polynomial in the large matrix limit is (up to some constant factor) given by the discontinuity of the Schwarz function of this polynomial curve.

http://arxiv.org/abs/0707.0425

5774. Filtering the Wright-Fisher diffusion

Author(s): Mireille Chaleyat-Maurel (MAP5 and PMA) and Valentine Genon- Catalot (MAP5)

Abstract: We consider a Wright-Fisher diffusion (x(t)) whose current state cannot be observed directly. Instead, at times t1 < t2 < . . ., the observations y(ti) are such that, given the process (x(t)), the random variables (y(ti)) are independent and the conditional distribution of y(ti) only depends on x(ti). When this conditional distribution has a specific form, we prove that the model ((x(ti), y(ti)), i 1) is a computable filter in the sense that all distributions involved in filtering, prediction and smoothing are exactly computable. These distributions are expressed as finite mixtures of parametric distributions. Thus, the number of statistics to compute at each iteration is finite, but this number may vary along iterations.

http://arxiv.org/abs/0707.0537

5775. Transformations of infinitely divisible distributions via improper stochastic integrals

Author(s): Ken-iti Sato

Abstract: Let $X^{(\mu)}(ds)$ be an $\mathbb{R}^d$-valued homogeneous independently scattered random measure over $\mathbb{R}$ having $\mu$ as the distribution of $X^{(\mu)}((t,t+1])$. Let $f(s)$ be a nonrandom measurable function on an open interval $(a,b)$ where $-\infty\leqslant a

http://arxiv.org/abs/0707.0538

5776. Infinite Horizon and Ergodic Optimal Quadratic Control for an Affine Equation with Stochastic Coefficients

Author(s): Giuseppina Guatteri and Federica Masiero

Abstract: We study quadratic optimal stochastic control problems with control dependent noise state equation perturbed by an affine term and with stochastic coefficients. Both infinite horizon case and ergodic case are treated. To this purpose we introduce a Backward Stochastic Riccati Equation and a dual backward stochastic equation, both considered in the whole time line. Besides some stabilizability conditions we prove existence of a solution for the two previous equations defined as limit of suitable finite horizon approximating problems. This allows to perform the synthesis of the optimal control.

http://arxiv.org/abs/0707.0606

5777. Transient NN random walk on the line

Author(s): Endre Cs\'aki and Ant\'onia F\"oldes and P\'al R\'ev\'esz

Abstract: We prove strong theorems for the local time at infinity of a nearest neighbor transient random walk. First, laws of the iterated logarithm are given for the large values of the local time. Then we investigate the length of intervals over which the walk runs through (always from left to right) without ever returning.

http://arxiv.org/abs/0707.0734

5778. Large Deviations Principle for Self-Intersection Local Times for simple random walk in dimension d>4

Author(s): Amine Asselah

Abstract: We obtain a large deviations principle for the self-intersection local times for a simple random walk in dimension d>4. As an application, we obtain moderate deviations for random walk in random sceneries in some region of parameters.

http://arxiv.org/abs/0707.0813

5779. The number of open paths in an oriented $\rho$-percolation model

Author(s): Francis Comets and Serguei Popov and Marina Vachkovskaia

Abstract: We study the asymptotic properties of the number of open paths of length $n$ in an oriented $\rho$-percolation model. We show that this number is $e^{n\alpha(\rho)(1+o(1))}$ as $n \to \infty$. The exponent $\alpha$ is deterministic, it can be expressed in terms of the free energy of a polymer model, and it can be explicitely computed in some range of the parameters. Moreover, in a restricted range of the parameters, we even show that the number of such paths is $n^{-1/2} W e^{n\alpha(\rho)}(1+o(1))$ for some nondegenerate random variable $W$. We build on connections with the model of directed polymers in random environment, and we use techniques and results developed in this context.

http://arxiv.org/abs/0707.0818

5780. A New Generalization of Chebyshev Inequality for Random Vectors

Author(s): Xinjia Chen

Abstract: In this article, we derive a new generalization of Chebyshev inequality for random vectors. We demonstrate that the new generalization is much less conservative than the classical generalization.

http://arxiv.org/abs/0707.0805

5781. Explicit Formula for Constructing Binomial Confidence Interval with Guaranteed Coverage Probability

Author(s): Xinjia Chen and Kemin Zhou and Jorge L. Aravena

Abstract: In this paper, we derive an explicit formula for constructing the confidence interval of binomial parameter with guaranteed coverage probability. The formula overcomes the limitation of normal approximation which is asymptotic in nature and thus inevitably introduce unknown errors in applications. Moreover, the formula is very tight in comparison with classic Clopper- Pearson's approach from the perspective of interval width. Based on the rigorous formula, we also obtain approximate formulas with excellent performance of coverage probability.

http://arxiv.org/abs/0707.0837

5782. Weighted lattice polynomials of independent random variables

Author(s): Jean-Luc Marichal

Abstract: We give the cumulative distribution functions, the expected values, and the moments of weighted lattice polynomials when regarded as real functions of independent random variables. Since weighted lattice polynomial functions include ordinary lattice polynomial functions and, particularly, order statistics, our results encompass the corresponding formulas for these particular functions. We also provide an application to the reliability analysis of coherent systems.

http://arxiv.org/abs/0707.0953

5783. The integral of the supremum process of Brownian motion

Author(s): Svante Janson and Niclas Petersson

Abstract: In this paper we study the integral of the supremum process of standard Brownian motion. We present an explicit formula for the moments of the integral (or area) A(T), covered by the process in the time interval [0,T]. The Laplace transform of A(T) follows as a consequence. The main proof involves a double Laplace transform of A(T) and is based on excursion theory and local time for Brownian motion.

http://arxiv.org/abs/0707.0989

5784. Tail estimates for the Brownian excursion area and other Brownian areas

Author(s): Svante Janson and Guy Louchard

Abstract: Several Brownian areas are considered in this paper: the Brownian excursion area, the Brownian bridge area, the Brownian motion area, the Brownian meander area, the Brownian double meander area, the positive part of Brownian bridge area, the positive part of Brownian motion area. We are interested in the asymptotics of the right tail of their density function. Inverting a double Laplace transform, we can derive, in a mechanical way, all terms of an asymptotic expansion. We illustrate our technique with the computation of the first four terms. We also obtain asymptotics for the right tail of the distribution function and for the moments. Our main tool is the two- dimensional saddle point method.

http://arxiv.org/abs/0707.0991

5785. Sharpness of the phase transition and exponential decay of the subcritical cluster size for percolation on quasi-transitive graphs

Author(s): Ton\'ci Antunovi\'c and Ivan Veseli\'c

Abstract: We study homogeneous, independent percolation on general quasi- transitive graphs. We prove that in the disorder regime where all clusters are finite almost surely, in fact the expectation of the cluster size is finite. This extends a well-known theorem by Menshikov and Aizenman & Barsky to all quasi-transitive graphs. Moreover we deduce that in this disorder regime the cluster size distribution decays exponentially, extending a result of Aizenman & Newman. Our results apply to both edge and site percolation, as well as long range (edge) percolation. The proof is based on a modification of the Aizenman & Barsky method.

http://arxiv.org/abs/0707.1089

5786. Gaussian Approximations of Multiple Integrals

Author(s): Giovanni Peccati (LSTA)

Abstract: Fix an integer k, and let I(l), l=1,2,..., be a sequence of k- dimensional vectors of multiple Wiener-It\^o integrals with respect to a general Gaussian process. We establish necessary and sufficient conditions to have that, as l diverges, the law of I(l) is asymptotically close (for example, in the sense of Prokhorov's distance) to the law of a k-dimensional Gaussian vector having the same covariance matrix as I(l). The main feature of our results is that they require minimal assumptions (basically, boundedness of variances) on the asymptotic behaviour of the variances and covariances of the elements of I(l). In particular, we will not assume that the covariance matrix of I(l) is convergent. This generalizes the results proved in Nualart and Peccati (2005), Peccati and Tudor (2005) and Nualart and Ortiz-Latorre (2007). As shown in Marinucci and Peccati (2007b), the criteria established in this paper are crucial in the study of the high-frequency behaviour of stationary fields defined on homogeneous spaces.

http://arxiv.org/abs/0707.1220

5787. Euler Scheme and Tempered Distributuions

Author(s): Julien Guyon (CERMICS)

Abstract: Given a smooth R^d-valued diffusion, we study how fast the Euler scheme with time step 1/n converges in law. To be precise, we look for which class of test functions f the approximate expectation E[f(X^{n,x}_1)] converges with speed 1/n to E[f(X^x_1)]. If X is uniformly elliptic, we show that this class contains all tempered distributions, and all measurable functions with exponential growth. We give applications to option pricing and hedging, proving numerical convergence rates for prices, deltas and gammas.

http://arxiv.org/abs/0707.1243

5788. Continuous first-passage percolation and continuous greedy

Author(s): Jean-Baptiste Gouere (MAPMO) and Regine Marchand (IECN)

Abstract: We study a random growth model on $\R^d$ introduced by Deijfen. This is a continuous first-passage percolation model. The growth occurs by means of spherical outbursts with random radii in the infected region. We aim at finding conditions on the distribution of the random radii to determine whether the growth of the process is linear or not. To do so, we compare this model with a continuous analogue of the greedy lattice paths model and transpose results in the lattice setting to the continuous setting.

http://arxiv.org/abs/0707.1395

5789. Conditional large and moderate deviations for sums of discrete random variables. Combinatoric applications

Author(s): Fabrice Gamboa (IMT) and Thierry Klein (IMT) and Cl\'ementine Prieur (IMT)

Abstract: We prove large and moderate deviation principles for the distribution of an empirical mean conditioned by the value of the sum of discrete i.i.d. random variables. Some applications for combinatoric problems are discussed.

http://arxiv.org/abs/0707.1461

5790. Non-Uniqueness of Gibbs measures relative to Brownian motion

Author(s): Volker Betz and Olaf Wittich

Abstract: We consider Gibbs measures relative to Brownian motion of Feynman- Kac type, with single site potential V. We show that for a large class of V, including the Coulomb potential, there exist infinitely many infinite volume Gibbs measures.

http://arxiv.org/abs/0707.1462

5791. On Connected Diagrams and Cumulants of Erdos-Renyi Matrix Models

Author(s): O. Khorunzhiy

Abstract: Regarding the adjacency matrices of n-vertex graphs and related graph Laplacian, we introduce two families of discrete matrix models constructed both with the help of the Erdos-Renyi ensemble of random graphs. Corresponding matrix sums represent the characteristic functions of the average number of walks and closed walks over the random graph. These sums can be considered as discrete analogs of the matrix integrals of random matrix theory. We study the diagram structure of the cumulant expansions of logarithms of these matrix sums and analyze the limiting expressions in the cases of constant and vanishing edge probabilities as n tends to infinity.

http://arxiv.org/abs/0707.0997

5792. Exchangeable partitions derived from Markovian coalescents with simultaneous multiple collisions

Author(s): Rui Dong

Abstract: Kingman derived the Ewens sampling formula for random partitions from the genealogy model defined by a Poisson process of mutations along lines of descent governed by a simple coalescent process. M\"ohle described the recursion which determines the generalization of the Ewens sampling formula when the lines of descent are governed by a coalescent with multiple collisions. In a recent work by Dong, Gnedin and Pitman, authors exploit an analogy with the theory of regenerative composition and partition structures, and provide various characterizations of the associated exchangeable random partitions. This paper gives parallel results for the further generalized model with lines of descent following a coalescent with simultaneous multiple collisions.

http://arxiv.org/abs/0707.1606

5793. Asymptotic regimes for the occupancy scheme of multiplicative cascades

Author(s): Jean Bertoin (PMA and Dma)

Abstract: In the classical occupancy scheme, one considers a fixed discrete probability measure ${\bf p}=(p_i: {i\in{\cal I}})$ and throws balls independently at random in boxes labeled by ${\cal I}$, such that p_i is the probability that a given ball falls into the box i. In this work, we are interested in asymptotic regimes of this scheme in the situation induced by a refining sequence $({\bf p}(k) : k\in\N)$ of random probability measures which arise from some multiplicative cascade. Our motivation comes from the study of the asymptotic behavior of certain fragmentation chains

http://arxiv.org/abs/0707.1640

5794. Statistical properties of a generalized threshold network model

Author(s): Yusuke Ide and Norio Konno and and Naoki Masuda

Abstract: The threshold network model is a type of finite random graphs. In this paper, we introduce a generalized threshold network model. A pair of vertices with random weights is connected by an edge when real-valued functions of the pair of weights belong to given Borel sets. We extend several known limit theorems for the number of prescribed subgraphs to show that the strong law of large numbers can be uniform convergence. We also prove two limit theorems for the local and global clustering coefficients.

http://arxiv.org/abs/0707.1744

5795. Random environment on coloured trees

Author(s): Mikhail Menshikov and Dimitri Petritis and Stanislav Volkov

Abstract: In this paper we study a regular rooted coloured tree with random labels assigned to its edges, where the distribution of the label assigned to an edge depends on the colours of its endpoints. We obtain some new results relevant to this model and also show how our model generalizes many other probabilistic models, including random walk in random environment on trees, recursive distributional equations, and multi-type branching random walk on $ \mathbb{R}$.

http://arxiv.org/abs/0707.1746

5796. Universal L^s -rate-optimality of L^r-optimal quantizers by dilatation and contraction

Author(s): Abass Sagna (PMA)

Abstract: Let $ r, s>0 $. For a given probability measure $P$ on $\mathbb{R} ^d$, let $(\alpha_n)_{n \geq 1}$ be a sequence of (asymptotically) $L^r(P)$- optimal quantizers. For all $\mu \in \mathbb{R}^d $ and for every $\theta >0 $, one defines the sequence $(\alpha_n^{\theta, \mu})_{n \geq 1}$ by : $ \forall n \geq 1, \alpha_n^{\theta, \mu} = \mu + \theta(\alpha_n - \mu) = \{\mu + \theta(a- \mu), a \in \alpha_n \} $. In this paper, we are interested in the asymptotics of the $L^s$-quantization error induced by the sequence $(\alpha_n^ {\theta, \mu})_{n \geq 1}$. We show that for a wide family of distributions, the sequence $(\alpha_n^{\theta, \mu})_{n \geq 1}$ is $L^s$-rate-optimal. For the Gaussian and the exponential distributions, one shows how to choose the parameter $\theta$ such that $(\alpha_n^{\theta, \mu})_{n \geq 1}$ satisfies the empirical measure theorem.

http://arxiv.org/abs/0707.1808

5797. On the girth of random Cayley graphs

Author(s): Alex Gamburd and Shlomo Hoory and Mehrdad Shahshahani and Aner Shalev, Balint Virag

Abstract: We prove that random d-regular Cayley graphs of the symmetric group asymptotically almost surely have girth at least (log_{d-1}|G|)^{1/2}/ 2 and that random d-regular Cayley graphs of simple algebraic groups over F_q asymptotically almost surely have girth at least log_{d-1}|G|/dim(G). For the symmetric p-groups the girth is between log log |G| and (log|G|) ^alpha with alpha<1. Several conjectures and open questions are presented.

http://arxiv.org/abs/0707.1833

5798. Determinantal transition kernels for some interacting particles on the line

Author(s): A. B. Dieker and J. Warren

Abstract: We find the transition kernels for four Markovian interacting particle systems on the line, by proving that each of these kernels is intertwined with a Karlin-McGregor type kernel. The resulting kernels all inherit the determinantal structure from the Karlin-McGregor formula, and have a similar form to Schutz's kernel for the totally asymmetric simple exclusion process.

http://arxiv.org/abs/0707.1843

5799. On a theorem in multi-parameter potential theory

Author(s): Ming Yang

Abstract: We prove a theorem on additive Levy processes and give applications

http://arxiv.org/abs/0707.1845

5800. On a general theorem for additive Levy processes

Author(s): Ming Yang

Abstract: We prove a new theorem on additive Levy processes and show that this theorem implies several proved theorems and a hard conjectured theorem.

http://arxiv.org/abs/0707.1847

5801. Hausdorrf dimension for level sets and k-multiple times

Author(s): Ming Yang

Abstract: We compute the Hausdorff dimension of the zero set of an additive Levy process.

http://arxiv.org/abs/0707.1849

5802. A new approach to the giant component problem

Author(s): Svante Janson and Malwina Luczak

Abstract: We study the largest component of a random (multi)graph on n vertices with a given degree sequence. We let n tend to infinity. Then, under some regularity conditions on the degree sequences, we give conditions on the asymptotic shape of the degree sequence that imply that with high probability all the components are small, and other conditions that imply that with high probability there is a giant component and the sizes of its vertex and edge sets satisfy a law of large numbers; under suitable assumptions these are the only two possibilities. In particular, we recover the results by Molloy and Reed on the size of the largest component in a random graph with a given degree sequence. We further obtain a new sharp result for the giant component just above the threshold, generalizing the case of G(n,p) with np=1+omega(n)n^ {-1/3}, where omega(n) tends to infinity arbitrarily slowly. Our method is based on the properties of empirical distributions of independent random variables, and leads to simple proofs.

http://arxiv.org/abs/0707.1786

5803. Law of iterated logarithm for NA sequences with non-identical distributions

Author(s): Guang-hui Cai and Hang Wu

Abstract: Based on a law of the iterated logarithm for independent random variables sequences, an iterated logarithm theorem for NA sequences with non- identical distributions is obtained. The proof is based on a Kolmogrov-type exponential inequality.

http://arxiv.org/abs/0707.1968

5804. Exit problems associated with affine reflection groups

Author(s): Yan Doumerc and John Moriarty

Abstract: We give the distribution of the first exit time of Brownian motion from the alcove of an affine Weyl group, in terms of the distributions of first exit times from simpler domains such as orthants. Applications are explicitly given in the different type cases. The results extend to any process for which the reflection arguments are valid. We also give the real eigenfunctions of the Laplacian for alcoves with Dirichlet and Neumann boundary conditions.

http://arxiv.org/abs/0707.2009

5805. A waiting time problem arising from the study of multi-stage carcinogenesis

Author(s): Rick Durrett and Deena Schmidt and and Jason Schweinsberg

Abstract: We consider the population genetics problem: How long does it take before some member of the population has m specified mutations? The case m=2 is relevant to onset of cancer due to the inactivation of both copies of a tumor suppressor gene. Models for larger m are needed for colon cancer and other diseases where a sequence of mutations leads to cells with uncontrolled growth.

http://arxiv.org/abs/0707.2057

5806. Approximate zero-one laws and sharpness of the percolation transition in a class of models including 2D Ising percolation

Author(s): Jacob van den Berg (CWI and VUA)

Abstract: One of the most well-known classical results for site percolation on the square lattice is the equation p_c + p_c^* = 1. In words, this equation means that for all values different from p_c of the parameter p the following holds: Either a.s. there is an infinite open cluster or a.s. there is an infinite closed `star' cluster. This result is closely related to the percolation transition being sharp: Below p_c the size of the open cluster of a given vertex is not only (a.s.) finite, but has a distrubtion with an exponential tail. The analog of this result has been proved by Higuchi in 1993 for two-dimensional Ising percolation, with fixed inverse temparature beta

http://arxiv.org/abs/0707.2077

5807. Representations of homogeneous quantum L\'evy fields

Author(s): V P Belavkin and L Gregory

Abstract: We study homogeneous quantum L\'{e}vy processes and fields with independent additive increments over a noncommutative *-monoid. These are described by infinitely divisible generating state functionals, invariant with respect to an endomorphic injective action of a symmetry semigroup. A strongly covariant GNS representation for the conditionally positive logarithmic functionals of these states is constructed in the complex Minkowski space in terms of canonical quadruples and isometric representations on the underlying pre- Hilbert field space. This is of much use in constructing quantum stochastic representations of homogeneous quantum L\'{e}vy fields on It\^{o} monoids, which is a natural algebraic way of defining dimension free, covariant quantum stochastic integration over a space-time indexing set.

http://arxiv.org/abs/0707.2142

5808. Malliavin calculus of Bismut type without probability

Author(s): Remi Leandre

Abstract: We translate in semigroup theory Bismut's way of the Malliavin calculus.

http://arxiv.org/abs/0707.2143

5809. Stochastic integral representations of quantum martingales on multiple Fock space

Author(s): Un Cig Ji

Abstract: In this paper a quantum stochastic integral representation theorem is obtained for unbounded regular martingales with respect to multidimensional quantum noise. This simultaneously extends results of Parthasarathy and Sinha to unbounded martingales and those of the author to multidimensions.

http://arxiv.org/abs/0707.2144

5810. The spectrum of heavy-tailed random matrices

Author(s): Gerard Ben Arous and Alice Guionnet

Abstract: Let $X_N$ be an $N\ts N$ random symmetric matrix with independent equidistributed entries. If the law $P$ of the entries has a finite second moment, it was shown by Wigner \cite{wigner} that the empirical distribution of the eigenvalues of $X_N$, once renormalized by $\sqrt{N}$, converges almost surely and in expectation to the so-called semicircular distribution as $N$ goes to infinity. In this paper we study the same question when $P$ is in the domain of attraction of an $\alpha$-stable law. We prove that if we renormalize the eigenvalues by a constant $a_N$ of order $N^{\frac{1}{\alpha}}$, the corresponding spectral distribution converges in expectation towards a law $\mu_\alpha$ which only depends on $\alpha$. We characterize $\mu_ \alpha$ and study some of its properties; it is a heavy-tailed probability measure which is absolutely continuous with respect to Lebesgue measure except possibly on a compact set of capacity zero.

http://arxiv.org/abs/0707.2159

5811. Weakly infinitely divisible measures on some locally compact Abelian groups

Author(s): Matyas Barczy and Gyula Pap

Abstract: On the torus group, on the group of p-adic integers and on the p-adic solenoid we give a construction of an arbitrary weakly infinitely divisible probability measure using real random variables. As a special case of our results, we have a new construction of the Haar measure on the p-adic solenoid.

http://arxiv.org/abs/0707.2186

5812. Probability Bracket Notation: Probability Space, Conditional Expectation and Introductory Martingales

Author(s): Xing M. Wang

Abstract: In this paper, we continue to explore the consistence and usability of Probability Bracket Notation (PBN) proposed in our previous articles. After a brief review of PBN with dimensional analysis, we investigate probability spaces in terms of PBN by introducing probability spaces associated with random variables (R.V) or associated with stochastic processes (S.P). Next, we express several important properties of conditional expectation (CE) and some their proofs in PBN. Then, we introduce martingales based on sequence of R.V or based on filtration in PBN. In the process, we see PBN can be used to investigate some probability problems, which otherwise might need explicit usage of Measure theory. Whenever applicable, we use dimensional analysis to validate our formulas and use graphs for visualization of concepts in PBN. We hope this study shows that PBN, stimulated by and adapted from Dirac notation in Quantum Mechanics (QM), may have the potential to be a useful tool in probability modeling, at least for those who are already familiar with Dirac notation in QM.

http://arxiv.org/abs/0707.2236

5813. Wigner theorems for random matrices with dependent entries: Ensembles associated to symmetric spaces and sample covariance matrices

Author(s): Katrin Hofmann-Credner and Michael Stolz

Abstract: It is a classical result of Wigner that for an hermitian matrix with independent entries on and above the diagonal, the mean empirical eigenvalue distribution converges weakly to the semicircle law as matrix size tends to infinity. In this paper, we prove analogs of Wigner's theorem for random matrices taken from all infinitesimal versions of classical symmetric spaces. This is a class of models which contains those studied by Wigner and Dyson, along with seven others arising in condensed matter physics. Like Wigner's, our results are universal in that they only depend on certain assumptions about the moments of the matrix entries, but not on the specifics of their distributions. What is more, we allow for a certain amount of dependence among the matrix entries, in the spirit of a recent generalization of Wigner's theorem, due to Schenker and Schulz-Baldes. As a byproduct, we obtain a universality result for sample covariance matrices with dependent entries.

http://arxiv.org/abs/0707.2333

5814. Negative dependence and the geometry of polynomials

Author(s): Julius Borcea and Petter Br\"and\'en and Thomas M. Liggett

Abstract: We introduce the class of {\em strongly Rayleigh} probability measures by means of geometric properties of their generating polynomials that amount to the stability of the latter. This class contains e.g. product measures, uniform random spanning tree measures, and large classes of determinantal probability measures and distributions for symmetric exclusion processes. We show that strongly Rayleigh measures enjoy all virtues of negative dependence and we also prove a series of conjectures due to Liggett, Pemantle, and Wagner, respectively. Moreover, we extend Lyons' recent results on determinantal probability measures and we construct counterexamples to several conjectures of Pemantle and Wagner on negative dependence and ultra log-concave rank sequences.

http://arxiv.org/abs/0707.2340

5815. From ballistic to diffusive behavior in periodic potentials

Author(s): Martin Hairer and Grigorios Pavliotis

Abstract: The long-time/large-scale, small-friction asymptotic for the one dimensional Langevin equation with a periodic potential is studied in this paper. It is shown that the Freidlin-Wentzell and central limit theorem (homogenization) limits commute. We prove that, in the combined small friction, long-time/large-scale limit the particle position converges weakly to a Brownian motion with a singular diffusion coefficient which we compute explicitly. We show that the same result is valid for a whole one parameter family of space/time rescalings. The proofs of our main results are based on some novel estimates on the resolvent of a hypoelliptic operator.

http://arxiv.org/abs/0707.2352

5816. Exact Computation of Minimum Sample Size for Estimation of Binomial Parameters

Author(s): Xinjia Chen

Abstract: It is a common contention that it is an ``impossible mission'' to exactly determine the minimum sample size for the estimation of a binomial parameter with prescribed margin of error and confidence level. In this paper, we investigate such a very old but also extremely important problem and demonstrate that the difficulty for obtaining the exact solution is not insurmountable. Unlike the classical approximate sample size method based on the central limit theorem, we develop a new approach for computing the minimum sample size that does not require any approximation. Moreover, our approach overcomes the conservatism of existing rigorous sample size methods derived from Bernoulli's theorem or Chernoff bounds. Our computational machinery consists of two essential ingredients. First, we prove that the minimum of coverage probability with respect to a binomial parameter bounded in an interval is attained at a discrete set of finite many values of the binomial parameter. This allows for reducing infinite many evaluations of coverage probability to finite many evaluations. Second, a recursive bounding technique is developed to further improve the efficiency of computation.

http://arxiv.org/abs/0707.2113

5817. Exact Computation of Minimum Sample Size for Estimating Proportion of Finite Population

Author(s): Xinjia Chen

Abstract: In this paper, we develop an exact method for the determination of the minimum sample size for the estimation of the proportion of a finite population with prescribed margin of error and confidence level. By characterizing the behavior of the coverage probability with respect to the proportion, we show that the computational complexity can be significantly reduced and bounded regardless population size.

http://arxiv.org/abs/0707.2115

5818. Exact Computation of Minimum Sample size for Estimation of Poisson Parameters

Author(s): Xinjia Chen

Abstract: In this paper, we develop an approach for the exact determination of the minimum sample size for the estimation of a Poisson parameter with prescribed margin of error and confidence level. The exact computation is made possible by reducing infinite many evaluations of coverage probability to finite many evaluations. Such reduction is based on our discovery that the minimum of coverage probability with respect to a Poisson parameter bounded in an interval is attained at a discrete set of finite many values.

http://arxiv.org/abs/0707.2116

5819. Nearly optimal embeddings of trees

Author(s): Benny Sudakov and Jan Vondrak

Abstract: In this paper we show how to find nearly optimal embeddings of large trees in several natural classes of graphs. The size of the tree T can be as large as a constant fraction of the size of the graph G, and the maximum degree of T can be close to the minimum degree of G. For example, we prove that any graph of minimum degree d without 4-cycles contains every tree of size \epsilon d^2 and maximum degree at most (1-2\epsilon)d - 2. As there exist d-regular graphs without 4-cycles of size O(d^2), this result is optimal up to constant factors. We prove similar nearly tight results for graphs of given girth, graphs with no complete bipartite subgraph K_{s,t}, random and certain pseudorandom graphs. These results are obtained using a simple and very natural randomized embedding algorithm, which can be viewed as a "self-avoiding tree-indexed random walk".

http://arxiv.org/abs/0707.2079

5820. A simple proof for the equivalence between invariance for stochastic and deterministic Systems

Author(s): Rainer Buckdahn and Marc Quincampoix and Catherine Rainer and Josef Teichmann

Abstract: We provide a short and elementary proof for the recently proved result by G. da Prato and H. Frankowska that a closed set is stochastically invariant if and only if it is deterministically invariant.

http://arxiv.org/abs/0707.2353

5821. On the linear fractional self-attracting diffusion

Author(s): Litan Yan and Yu Sun and Yunsheng Lu

Abstract: In this paper, we introduce the linear fractional self-attracting diffusion driven by a fractional Brownian motion with Hurst index 1/2

http://arxiv.org/abs/0707.2627

5822. Iterated logarithm law for anticipating stochastic differential equations

Author(s): D. Marquez-Carreras and C. Rovira

Abstract: We prove a functional law of iterated logarithm for the following kind of anticipating stochastic differential equations $$\xi^u_t=X_0^u+\frac{1}{\sqrt{\log\log u}}\sum_{j=1}^k \int_0^{t} A_j^u(\xi^u_s)\circ dW_{s}^j+ \int_0^{t} A_0^u(\xi^u_s)ds,$$ where $u>e$, $W=\{(W_t^1,...,W_t^k), 0\le t\le 1\}$ is a standard $k$-dimensional Wiener process, $A_0^u,A_1^u,..., A_k^u:\mathbb{R}^d\longrightarrow \mathbb {R}^d$ are functions of class $\mathcal{C}^2$ with bounded partial derivatives up to order 2, $X_0^u$ is a random vector not necessarily adapted and the first integral is a generalized Stratonovich integral .

http://arxiv.org/abs/0707.2650

5823. A Finite Horizon Optimal Multiple Switching Problem

Author(s): Boualem Djehiche and Said Hamadene and Alexandre Popier

Abstract: We consider the problem of optimal multiple switching in finite horizon, when the state of the system, including the switching costs, is a general adapted stochastic process. The problem is formulated as an extended impulse control problem and completely solved using probabilistic tools such as the Snell envelop of processes and reflected backward stochastic differential equations. Finally, when the state of the system is a Markov diffusion process, we show that the vector of value functions of the optimal problem is a viscosity solution to a system of variational inequalities with inter-connected obstacles.

http://arxiv.org/abs/0707.2663

5824. Nonlinear SDEs driven by L\'evy processes and related PDEs

Author(s): Benjamin Jourdain (CERMICS) and Sylvie M\'el\'eard (CMAP) and Wojbor Woyczynski

Abstract: In this paper we study general nonlinear stochastic differential equations, where the usual Brownian motion is replaced by a L\'evy process. We also suppose that the coefficient multiplying the increments of this process is merely Lipschitz continuous and not necessarily linear in the time- marginals of the solution as is the case in the classical McKean-Vlasov model. We first study existence, uniqueness and particle approximations for these stochastic differential equations. When the driving process is a pure jump L \'evy process with a smooth but unbounded L\'evy measure, we develop a stochastic calculus of variations to prove that the time-marginals of the solutions are absolutely continuous with respect to the Lebesgue measure. In the case of a symmetric stable driving process, we deduce the existence of a function solution to a nonlinear integro-differential equation involving the fractional Laplacian.

http://arxiv.org/abs/0707.2723

5825. The equilibrium states for semigroups of rational maps

Author(s): Hiroki Sumi and Mariusz Urbanski

Abstract: We consider the dynamics of skew product maps associated with finitely generated semigroups of rational maps on the Riemann sphere. We show that under some conditions on the dynamics and the potential function \psi, there exists a unique equilibrium state for \psi and a unique $\exp(\P(\psi)-\psi)$- conformal measure, where P(\psi) denotes the topological pressure of \psi.

http://arxiv.org/abs/0707.2444

5826. Real analyticity of Hausdorff dimension for expanding rational semigroups

Author(s): Hiroki Sumi and Mariusz Urbanski

Abstract: We consider the dynamics of expanding semigroups generated by finitely many rational maps on the Riemann sphere. We show that for an analytic family of such semigroups, the Bowen parameter function is real-analytic and plurisubharmonic. Combining this with a result obtained by the first author, we show that if for each semigroup of such an analytic family of expanding semigroups satisfies the open set condition, then the function of the Hausdorff dimension of the Julia set is real-analytic and plurisubharmonic. Moreover, we provide an extensive collection of classes of examples of analytic families of semigroups satisfying all the above conditions and we analyze in detail the corresponding Bowen's parameters and Hausdorff dimension function.

http://arxiv.org/abs/0707.2447

5827. Random perturbations of stochastic chains with unbounded variable length memory

Author(s): Pierre Collet and Antonio Galves and Florencia G. Leonardi

Abstract: We consider binary infinite order stochastic chains perturbed by a random noise. This means that at each time step, the value assumed by the chain can be randomly and independently flipped with a small fixed probability. We show that the transition probabilities of the perturbed chain are uniformly close to the corresponding transition probabilities of the original chain. As a consequence, in the case of stochastic chains with unbounded but otherwise finite variable length memory, we show that it is possible to recover the context tree of the original chain, using a suitable version of the algorithm Context, provided that the noise is small enough.

http://arxiv.org/abs/0707.2796

5828. Poincar\'e inequality for non euclidean metrics and transportation cost inequalities on $\mathbb{R}^d$

Author(s): Nathael Gozlan (LAMA)

Abstract: In this paper, we consider Poincar\'e inequalities for non euclidean metrics on $\mathbb{R}^d$. These inequalities enable us to derive precise dimension free concentration inequalities for product measures. This technique is appropriate for a large scope of concentration rate: between exponential and gaussian and beyond. We give different equivalent functional forms of these Poincar\'e type inequalities in terms of transportation-cost inequalities and infimum convolution inequalities. Workable sufficient conditions are given and a comparison is made with generalized Beckner-Latala-Oleszkiewicz inequalities.

http://arxiv.org/abs/0707.2834

5829. Critical percolation on random regular graphs

Author(s): Asaf Nachmias and Yuval Peres

Abstract: We describe the component sizes in critical independent p-bond percolation on a random d-regular graph on n vertices, where d is fixed and n grows. We prove mean-field behavior around the critical probability p_c=1/(d-1). In particular, we show that there is a scaling window of width n^ {-1/3} around p_c in which the sizes of the largest components are roughly n^ {2/3} and we describe their limiting joint distribution. We also show that for the subcritical regime, i.e. p = (1-eps(n))p_c where eps(n)=o(1) but \eps (n)n^{1/3} tends to infinity, the sizes of the largest components are concentrated around an explicit function of n and eps(n) which is of order o(n^{2/3}). In the supercritical regime, i.e. p = (1+\eps(n))p_c where eps(n)=o(1) but eps(n)n^{1/3} tends to infinity, the size of the largest component is concentrated around the value (2d/(d-2))\eps(n)n and a duality principle holds: other component sizes are distributed as in the subcritical regime.

http://arxiv.org/abs/0707.2839

5830. Geography of local configurations

Author(s): David Coupier

Abstract: A $d$-dimensional ferromagnetic Ising model on a lattice torus is considered. As the size $n$ of the lattice tends to infinity, the magnetic field $a=a(n)$ and the pair potential $b=b(n)$ depend on $n$. Precise bounds for the probability for local configurations to occur in a large ball are given. Under some conditions bearing on potentials $a(n)$ and $b(n)$, the distance between copies of different local configurations is estimated according to their weights. Finally, a sufficient condition ensuring that a given local configuration occurs everywhere in the lattice is suggested.

http://arxiv.org/abs/0707.2889

5831. Some particular self-interacting diffusions: ergodic behavior and almost sure convergence

Author(s): Sebastien Chambeu and Aline Kurtzmann

Abstract: This paper is concerned with some self-interacting diffusions $ (X_t,t\geq 0)$ living on $\mathbb{R}^d$. These diffusions are solutions to stochastic differential equations: $$\mathrm{d}X_t = \mathrm{d}B_t - g(t)\nabla V (X_t - \bar{\mu}_t) \mathrm{d}t,$$ where $\bar{\mu}_t$ is the mean of the empirical measure of the process $X$, $V$ is an asymptotically strictly convex potential and $g$ is a given function. We study the ergodic behavior of $X$ and prove that it is strongly related to $g$. Actually, we will show that $X$ and $\bar{\mu}_t$ have the same asymptotic behavior and we will give necessary and sufficient conditions (on $g$ and $V$) for the almost sure convergence of $X$.

http://arxiv.org/abs/0707.2908

5832. Convergence in distribution of some particular self-interacting diffusions: the simulated annealing method

Author(s): Sebastien Chambeu and Aline Kurtzmann

Abstract: The present paper is concerned with some self-interacting diffusions $(X_t,t\geq 0)$ living on $\mathbb{R}^d$. These diffusions are solutions to stochastic differential equations: $$\mathrm{d}X_t = \mathrm{d}B_t - g (t)\nabla V(X_t - \bar{\mu}_t) \mathrm{d}t$$ where $\bar{\mu}_t$ is the empirical mean of the process $X$, $V$ is an asymptotically strictly convex potential and $g$ is a given function. The authors have still studied the ergodic behavior of $X$ and proved that it is strongly related to $g$. We go further and give necessary and sufficient conditions (for small $g$'s) in order that $X$ converges in probability to $X_\infty$ (which is related to the global minima of $V $).

http://arxiv.org/abs/0707.2910

5833. Minimum Coverage Probabilities of Confidence Intervals

Author(s): Xinjia Chen

Abstract: By our recently developed techniques, we have shown that the minimum coverage probability of an open binomial confidence interval with respect to the corresponding binomial parameter is achieved at a discrete set of finite many values. Moreover, we have obtained similar results for the case of Poisson confidence interval and the case of confidence interval for the proportion of finite population.

http://arxiv.org/abs/0707.2814

5834. Probability Bracket Notation, Probability Vectors, Markov Chains and Stochastic Processes

Author(s): Xing M. Wang

Abstract: Dirac notation has been widely used for vectors in Hilbert spaces of Quantum Theories. It now has also been introduced to Information Retrieval. In this paper, we propose a new set of symbols, the Probability Bracket Notation (PBN), for representation of probability theories. The new are defined similarly (but not identically) as their counterparts in Dirac notation, which we refer as Vector Bracket Notation (VBN). By using PBN to represent fundamental definitions and theorems for discrete and continuous random variables, we show that PBN could play a similar role in probability sample space as Dirac notation in Hilbert space. We also find that there is a close relation between our probability state kets and probability vectors in Markov chains. In the end, we apply PBN to some important stochastic processes, and present the time evolution differential equations (TEDE) of time-continuous Markov chains in both Heisenberg and Schrodinger pictures. We summarize the similarities and differences between PBN and VBN in the two tables of Appendix A.

http://arxiv.org/abs/cs/0702021

5835. Induced Hilbert Space, Markov Chain, Diffusion Map and Fock Space in Thermophysics

Author(s): Xing M. Wang

Abstract: In this article, we continue to explore Probability Bracket Notation (PBN), proposed in our previous article. Using both Dirac vector bracket notation (VBN) and PBN, we define induced Hilbert space and induced sample space, and propose that there exists an equivalence relation between a Hilbert space and a probability sample space constructed from the same base observable (s). Then we investigate Markov transition matrices and their eigenvectors to make diffusion maps with two examples: a simple graph theory example, to serve as a prototype of bidirectional transition operator; a famous text document example in IR literature, to serve as a tutorial of diffusion map in text document space. We notice that, in both examples, the sample space of the Markov chain and the Hilbert space spanned by the eigenvectors of the transition matrix are not equivalent. At the end, we apply our PBN and equivalence proposal to Thermophysics by associating phase space with Hilbert space or Fock space of many-particle systems.

http://arxiv.org/abs/cs/0702121

5836. A Note on the Pfaffian Integration Theorem

Author(s): Alexei Borodin and Eugene Kanzieper

Abstract: Two alternative, fairly compact proofs are presented of the Pfaffian integration theorem that surfaced in the recent studies of spectral properties of Ginibre's Orthogonal Ensemble. The first proof is based on a concept of the Fredholm Pfaffian; the second proof is purely linear-algebraic.

http://arxiv.org/abs/0707.2784

5837. Card Shuffling and Diophantine Approximation

Author(s): Omer Angel and Yuval Peres and David B. Wilson

Abstract: The ``overlapping-cycles shuffle'' mixes a deck of n cards by moving either the nth card or the (n-k)th card to the top of the deck, with probability half each. We determine the spectral gap for the location of a single card, which, as a function of k and n, has surprising behavior. For example, suppose k is the closest integer to alpha n for a fixed real alpha in (0,1). Then for rational alpha the spectral gap is Theta(n^{-2}), while for poorly approximable irrational numbers alpha, such as the reciprocal of the golden ratio, the spectral gap is Theta(n^{-3/2}).

http://arxiv.org/abs/0707.2994

5838. Finding Efficient Recursions for Risk Aggregation by Computer Algebra

Author(s): S. Gerhold and R. Warnung

Abstract: We derive recursions for the probability distribution of random sums by computer algebra. Unlike the well-known Panjer-type recursions, they are of finite order and thus allow for computation in linear time. This efficiency is bought by the assumption that the probability generating function of the claim size be algebraic. The probability generating function of the claim number is supposed to be from the rather general class of D-finite functions.

http://arxiv.org/abs/0707.3028

5839. The coding complexity of L\'evy processes

Author(s): Frank Aurzada and Steffen Dereich

Abstract: We investigate the high resolution coding problem for general real- valued L\'evy processes under L^p[0,1]-norm distortion. Tight asymptotic formulas are found under mild regularity assumptions.

http://arxiv.org/abs/0707.3040

5840. A Random Change of Variables and Applications to the Stochastic Porous Medium Equation with Multiplicative Time Noise

Author(s): S. V. Lototsky

Abstract: A change of variables is introduced to reduce certain nonlinear stochastic evolution equations with multiplicative noise to the corresponding deterministic equation. The result is then used to investigate a stochastic porous medium equation.

http://arxiv.org/abs/0707.3155

5841. Random Walks in Random Environments

Author(s): L. V. Bogachev

Abstract: Random walks provide a simple conventional model to describe various transport processes, for example propagation of heat or diffusion of matter through a medium. However, in many practical cases the medium is highly irregular due to defects, impurities, fluctuations etc., and it is natural to model this as random environment. In the random walks context, such models are referred to as Random Walks in Random Environments (RWRE). This is a relatively new chapter in applied probability and physics of disordered systems, initiated in the 1970s. Early interest was motivated by some problems in biology, crystallography and metal physics, but later applications have spread through numerous areas. After 30 years of extensive work, RWRE remain a very active area of research, which has already led to many surprising discoveries. The goal of this article is to give a brief introduction to the beautiful area of RWRE. The principal model to be discussed is a random walk with nearest-neighbor jumps in independent identically distributed (i.i.d.) random environment in one dimension, although we shall also comment on some extensions and generalizations. The focus is on rigorous results; however, heuristics is used freely to motivate the ideas and explain the approaches and proofs. In a few cases, sketches of the proofs have been included, which should help the reader to appreciate the flavor of results and methods.

http://arxiv.org/abs/0707.3160

5842. Estimates for the diameter of a chordal SLE path

Author(s): Tom Alberts (New York University) and Michael J. Kozdron (University of Regina)

Abstract: We derive an estimate for the diameter of a chordal SLE path in the upper half plane H between two real boundary points 0 and x>0. In particular, we prove that if 0 < kappa < 8 and gamma:[0,1] to closure(H) is a chordal SLE in H from 0 to x, then P(gamma[0,1] cap C_R neq emptyset) asymp R^(1-4a) where a=2/kappa and C_R denotes the circle of radius Rx centred at 0 in the upper half plane. As an application of our result, we derive an estimate that two nearby points, one on the boundary and one in the interior, are swallowed together by a chordal SLE path, 4 < kappa <8.

http://arxiv.org/abs/0707.3163

5843. The barnes G function and its relations with sums and products of generalized Gamma convolution variables

Author(s): Ashkan Nikeghbali and Marc Yor

Abstract: We give a probabilistic interpretation for the Barnes G-function which appears in random matrix theory and in analytic number theory in the important moments conjecture due to Keating-Snaith for the Riemann zeta function, via the analogy with the characteristic polynomial of random unitary matrices. We show that the Mellin transform of the characteristic polynomial of random unitary matrices and the Barnes G-function are intimately related with products and sums of gamma, beta and log-gamma variables. In particular, we show that the law of the modulus of the characteristic polynomial of random unitary matrices can be expressed with the help of products of gamma or beta variables, and that the reciprocal of the Barnes G-function has a L\'{e}vy-Khintchin type representation. These results lead us to introduce the so called generalized gamma convolution variables.

http://arxiv.org/abs/0707.3187

5844. Growth-optimal portfolios under transaction costs

Author(s): Jan Palczewski and Lukasz Stettner

Abstract: This paper studies a portfolio optimization problem in a discrete- time Markovian model of a financial market, in which asset price dynamics depend on an external process of economic factors. There are transaction costs with a structure that covers, in particular, the case of fixed plus proportional costs. We prove that there exists a self-financing trading strategy maximizing the average growth rate of the portfolio wealth. We show that this strategy has a Markovian form. Our result is obtained by large deviations estimates on empirical measures of the price process and by a generalization of the vanishing discount method to discontinuous transition operators.

http://arxiv.org/abs/0707.3198

5845. Gibbs Rapidly Samples Colorings of G(n,d/n)

Author(s): Elchanan Mossel and Allan Sly

Abstract: Gibbs sampling also known as Glauber dynamics is a popular technique for sampling high dimensional distributions defined on graphs. Of special interest is the behavior of Gibbs sampling on the Erd\H{o}s-R\'enyi random graph G(n,d/n). While the average degree in G(n,d/n) is d(1-o(1)), it contains many nodes of degree of order $\log n / \log \log n$. The existence of nodes of almost logarithmic degrees implies that for many natural distributions defined on G(n,p) such as uniform coloring or the Ising model, the mixing time of Gibbs sampling is at least $n^{1 + \Omega (1 / \log \log n)}$. High degree nodes pose a technical challenge in proving polynomial time mixing of the dynamics for many models including coloring. In this work consider sampling q-colorings and show that for every $d < \infty$ there exists $q(d) < \infty$ such that for all $q \geq q(d)$ the mixing time of Gibbs sampling on G(n,d/n) is polynomial in $n$ with high probability. Our results are the first polynomial time mixing results proven for the coloring model on G(n,d/n) for d > 1 where the number of colors does not depend on n. They extend to much more general families of graphs which are sparse in some average sense and to much more general interactions. The results also generalize to the hard-core model at low fugacity and to general models of soft constraints at high temperatures.

http://arxiv.org/abs/0707.3241

5846. On the irrelevant disorder regime of pinning models

Author(s): G. Giacomin (1) and F. L. Toninelli (2) ((1) Universite' de Paris 7, (2) Laboratoire de Physique, ENS Lyon and CNRS)

Abstract: Recent results have lead to substantial progress in understanding the role of disorder in the (de)localization transition of polymer pinning models. Notably, there is an understanding of the crucial issue of disorder relevance and irrelevance that, albeit still partial, is now rigorous. In this work we exploit interpolation and replica coupling methods to get sharper results on the irrelevant disorder regime of pinning models. In particular, we compute in this regime the first order term in the expansion of the free energy close to criticality, which coincides with the first order of the formal expansion obtained by field theory methods. We also show that the quenched and the quenched averaged correlation length exponents coincide, while in general they are expected to be different. Interpolation and replica coupling methods in this class of models naturally lead to studying the behavior of the intersection of certain renewal sequences and one of the main tools in this work is precisely renewal theory and the study of these intersection renewals.

http://arxiv.org/abs/0707.3340

5847. On a Gibbs characterization of normalized generalized Gamma processes

Author(s): Annalisa Cerquetti

Abstract: We show that a Gibbs characterization of normalized generalized Gamma processes, recently obtained in Lijoi, Pr\"unster and Walker (2007), can alternatively be derived by exploiting a characterization of exponentially tilted Poisson-Kingman models stated in Pitman (2003). We also provide a completion of this result investigating the existence of normalized random measures inducing exchangeable Gibbs partitions of type $\alpha \in (- \infty, 0]$.

http://arxiv.org/abs/0707.3408

5848. Serial interval contraction during epidemics

Author(s): Eben Kenah and Marc Lipsitch and James M. Robins

Abstract: The serial interval may be defined as the time between the onset of symptoms in an infectious person and the onset of symptoms in a person he or she infects. Several methods of analyzing epidemic data, such as estimates of reproductive numbers, are based on a probability distribution for the serial interval. In this paper, we specify a general SIR epidemic model and prove that the mean serial interval must contract when susceptible persons are at risk of multiple infectious contacts. In an epidemic, the mean serial interval contracts as the prevalence of infection increases. We illustrate two mechanisms through which serial interval contraction can occur: In global competition among infectious contacts, risk of multiple infectious contacts results from a high global prevalence of infection. In local competition among infectious contacts, clustering of contacts places susceptible persons at risk of multiple infectious contacts even when the global prevalence of infection is low. We illustrate these patterns with simulations. We also find that the minimum mean serial interval in a compartmental SIR model becomes arbitrarily small with sufficiently high R_{0}. We conclude that the serial interval distribution is not a stable characteristic of an infectious disease.

http://arxiv.org/abs/0706.2024

5849. Measure-valued equations for Kolmogorov operators with unbounded coefficients

Author(s): Luigi Manca

Abstract: Given a real and separable Hilbert space H we consider the measure- valued equation \begin{equation*} \int_H\phi(x)\mu_t(dx)- \int_H\phi(x)\mu(dx)= \int_0^t(\int_HK_0\phi(x)\mu_s(dx))ds, \end{equation*} where K_0 is the Kolmogorov differential operator \[ K_0\phi(x)=\frac12\textrm{Trace}\big[BB^*D^2\phi(x)\big]+< x,A^*D \phi(x)>+< D\phi(x),F(x)>, \] $x\in H$, $\phi:H\to \Rset$ is a suitable smooth function, $A:D(A)\subset H\to H $ is linear, $F:H\to H$ is a globally Lipschitz function and $B:H\to H$ is linear and continuous. In order prove existence and uniqueness of a solution for the above equation, we show that $K_0$ is a core, in a suitable way, of the infinitesimal generator associated to the solution of a certain stochastic differential equation in H. We also extend the above results to a reaction-diffusion operator with polinomial nonlinearities.

http://arxiv.org/abs/0707.3233

5850. Limit laws for boolean convolutions

Author(s): Jiun-Chau Wang

Abstract: We study the distributional behavior for products, and for sums of boolean independent random variables in an infinitesimal triangular array. We show that the limit laws of boolean convolutions are determined by the limit laws of free convolutions, and vice versa. We further use these results to show several connections between the limiting distributional behavior of classical convolutions and that of boolean convolutions. The proof of our results is based on the analytical apparatus developed for free convolutions.

http://arxiv.org/abs/0707.3401

5851. When almost all sets are difference dominated

Author(s): Peter Hegarty and Steven J. Miller

Abstract: We investigate the relationship between the sizes of the sum and difference sets attached to a subset of {0,1,...,N}, chosen randomly according to a binomial model with parameter p(N), with N^{-1} = o(p(N)). We show that the random subset is almost surely difference dominated, as $N \to \infty $, for any choice of p(N) tending to zero, confirming a conjecture of Martin and O'Bryant. We exhibit a threshold phenomenon regarding the ratio of the size of the difference- to the sumset. If p(N) = o(N^{-1/2}) then almost all sums and differences in the random subset are almost surely distinct, and the difference set is almost surely about twice as large as the sumset. If N^{-1/2} = o(p(N)) then both the sum and difference sets almost surely have size $(2N+1) - (p(N)^{-2})$, and so the ratio in question is almost surely very close to one. If $p(N) = c \cdot N^{-1/2}$ then as c increases from zero to infinity (i.e.: as the threshold is crossed), the same ratio almost surely decreases continuously from two to one according to an explicitly given function of c. We extend our results to the comparison of the generalized difference sets attached to an arbitrary pair of binary linear forms. For certain pairs of forms we show that there is a sharp threshold such that one form almost surely dominates below the threshold, and the other almost surely above it. The heart of our approach involves proving strong concentration of the sizes of the sum and difference sets about their mean values.

http://arxiv.org/abs/0707.3417

5852. Convergence in law for certain weighted quadratic variations of fractional Brownian motion

Author(s): Ivan Nourdin (PMA) and David Nualart

Abstract: By means of Malliavin calculus, we prove the convergence in law for certain weighted quadratic variations of a fractional Brownian motion B with Hurst index H between 1/4 and 1/2.

http://arxiv.org/abs/0707.3448

5853. Limit theorems for conditioned multitype Dawson-Watanabe processes

Author(s): Nicolas Champagnat (INRIA Sophia Antipolis / INRIA Lorraine / IECN), Sylvie Roelly

Abstract: A multitype Dawson-Watanabe process is conditioned, in subcritical and critical cases, on non-extinction in the remote future. On every finite time interval, its distribution is absolutely continuous with respect to the law of the unconditioned process. A martingale problem characterization is also given. The explicit form of the Laplace functional of the conditioned process is used to obtain several results on the long time behaviour of the mass of the conditioned and unconditioned processes. The general case is considered first, where the mutation matrix which modelizes the interaction between the types, is irreducible. Several two-type models with decomposable mutation matrices are also analysed.

http://arxiv.org/abs/0707.3504

5854. Upper bound of loss probability in an OFDMA system with randomly located users

Author(s): Laurent Decreusefond (LTCI) and Eduardo Ferraz (LTCI) and Philippe Martins (LTCI)

Abstract: For OFDMA systems, we find a rough but easily computed upper bound for the probability of loosing communications by insufficient number of sub- channels on downlink. We consider as random the positions of receiving users in the system as well as the number of sub-channels dedicated to each one. We use recent results of the theory of point processes which reduce our calculations to the first and second moments of the total required number of sub-carriers.

http://arxiv.org/abs/0707.3509

5855. Exchangeable Random Networks

Author(s): F. Bassetti and M. Cosentino Lagomarsino and S. Mandr\'a

Abstract: We introduce and study a class of exchangeable random graph ensembles. They can be used as statistical null models for empirical networks, and as a tool for theoretical investigations. We provide general theorems that carachterize the degree distribution of the ensemble graphs, together with some features that are important for applications, such as subgraph distributions and kernel of the adjacency matrix. These results are used to compare to other models of simple and complex networks. A particular case of directed networks with power-law out--degree is studied in more detail, as an example of the flexibility of the model in applications.

http://arxiv.org/abs/0707.3545

5856. Singular measures of circle homeomorphisms with two break points

Author(s): Akhtam Dzhalilov and Isabelle Liousse and Dieter Mayer

Abstract: Let $T_{f}$ be a circle homeomorphism with two break points $a_ {b},c_{b}$ and irrational rotation number $\varrho_{f}$. Suppose that the derivative $Df$ of its lift $f$ is absolutely continuous on every connected interval of the set $S^{1}\backslash\{a_{b},c_{b}\}$, that $DlogDf \in L^{1}$ and the product of the jump ratios of $ Df $ at the break points is nontrivial, i.e. $\frac{Df_{-}(a_{b})}{Df_{+}(a_{b})}\frac{Df_{-}(c_{b})}{Df_{+}(c_ {b})}\neq1$. We prove that the unique $T_{f}$- invariant probability measure $\mu_ {f}$ is then singular with respect to Lebesgue measure $l$ on $S^{1}$.

http://arxiv.org/abs/0707.3528

5857. On the Hausdorff dimension of invariant measures of weakly contracting on average measurable IFS

Author(s): Joanna Jaroszewska and Michal Rams

Abstract: We consider measures which are invariant under a measurable iterated function system with positive, place-dependent probabilities in a separable metric space. We provide an upper bound of the Hausdorff dimension of such a measure if it is ergodic. We also prove that it is ergodic iff the related skew product is.

http://arxiv.org/abs/0707.3532

5858. Scaling limits for random fields with long-range dependence

Author(s): Ingemar Kaj and Lasse Leskel\"a and Ilkka Norros and Volker Schmidt

Abstract: This paper studies the limits of a spatial random field generated by uniformly scattered random sets, as the density $\lambda$ of the sets grows to infinity and the mean volume $\rho$ of the sets tends to zero. Assuming that the volume distribution has a regularly varying tail with infinite variance, we show that the centered and renormalized random field can have three different limits, depending on the relative speed at which $\lambda$ and $\rho$ are scaled. If $\lambda$ grows much faster than $\rho$ shrinks, the limit is Gaussian with long-range dependence, while in the opposite case, the limit is independently scattered with infinite second moments. In a special intermediate scaling regime, there exists a nontrivial limiting random field that is not stable.

http://arxiv.org/abs/0707.3729

5859. Malliavin calculus and Clark-Ocone formula for functionals of a square-integrable L\'evy process

Author(s): Jean-Fran\c{c}ois Renaud and Bruno R\'emillard

Abstract: In this paper, we construct a Malliavin derivative for functionals of square-integrable L\'evy processes and derive a Clark-Ocone formula. The Malliavin derivative is defined via chaos expansions involving stochastic integrals with respect to Brownian motion and Poisson random measure. As an illustration, we compute the explicit martingale representation for the maximum of a L\'evy process.

http://arxiv.org/abs/0707.3734

5860. Ergodic properties of Poissonian ID processes

Author(s): Emmanuel Roy

Abstract: We show that a stationary IDp process (i.e., an infinitely divisible stationary process without Gaussian part) can be written as the independent sum of four stationary IDp processes, each of them belonging to a different class characterized by its L\'{e}vy measure. The ergodic properties of each class are, respectively, nonergodicity, weak mixing, mixing of all order and Bernoullicity. To obtain these results, we use the representation of an IDp process as an integral with respect to a Poisson measure, which, more generally, has led us to study basic ergodic properties of these objects.

http://arxiv.org/abs/0707.3746

5861. Exponential inequalities for self-normalized martingales with applications

Author(s): Bernard Bercu (IMB) and Abderrahmen Touati (IMB)

Abstract: We propose several exponential inequalities for self-normalized martingales similar to those established by De la Pena. The keystone is the introduction of a new notion of random variable heavy on left or right. Applications associated with linear regressions, autoregressive and branching processes are also provided.

http://arxiv.org/abs/0707.3715

5862. Occupation Statistics of Critical Branching Random Walks

Author(s): Steven Lalley and Xinghua Zheng

Abstract: We consider a critical nearest neighbor branching random walk on the $d-$dimensional integer lattice. Denote by $V_m$ the maximal number of particles at a single site at time $m$, and by $G_{m}$ the event that the branching random walk survives to generation $m$. We show that if the offspring distribution has finite $n$-th moment, then in dimensions $d\geq 3$, conditional on $G_{m}$, $V_m=O_p(m^{\frac{1}{n}})$; and if the offspring distribution has exponentially decaying tail, then, conditional on $G_ {m}$, (a) $V_m=O_p(\log m)$ in dimensions $d\geq 3$, and (b) $V_m=O_p((\log m) ^2)$ in dimension $d=2$. On the other hand, we show that if the offspring distribution is non-degenerate then $P(V_m\geq \delta \log m | G_{m})\to 1$ for some $\delta > 0$. Therefore, in dimensions $d\geq 3$, if the offspring > distribution has exponentially decaying tail then conditional on $G_{m}$, the distribution of ${V_m}/{\log m}$ must converge to a nontrivial limit as $m \to \infty$. Furthermore, we show that, conditional on $G_{m}$, in dimensions $d \geq 3$, the number of multiplicity-$j$ sites, $j\geq 1$, and the number of occupied sites, normalized by $m$, converge jointly to multiples of an exponential random variable; in dimension $d=2$, however, the number of particles on a `typical' site is $O_p(\log m)$, and the number of occupied sites is $O_p(m/ \log m).$

http://arxiv.org/abs/0707.3829

5863. Effective resistance on random electrical networks

Author(s): Michel Benaim and Itai Benjamini and Raphael Rossignol

Abstract: Take a big graph and make a random electrical network of it by assigning independent resistances on its edges. Now, ask for the behaviour of the effective resistance between two vertices (two ``poles'') far apart. We assume in general that resistances are bounded away from 0 and infinity. In this paper, we study three cases of effective resistance in such random electrical networks: from one side to another in a box of $Z^d$, between two points in $Z^2$, and between two points on a cylinder graph $GxZ$. For all these cases, we obtain the right order of the fluctuations when the poles move apart from each other, and give corresponding subgaussian concentration inequalities. For the cylinder graphs, we prove two additional results: a central limit theorem and a result of uniform stability with respect to noise.

http://arxiv.org/abs/0707.3837

5864. Stochastic evolution equations for nonlinear filtering of random fields in the presence of fractional Brownian sheet observation noise

Author(s): Anna Amirdjanova and Matthew Linn

Abstract: The problem of nonlinear filtering of a random field observed in the presence of a noise, modeled by a persistent fractional Brownian sheet of Hurst index $(H_1,H_2)$ with $0.5

http://arxiv.org/abs/0707.3856

5865. Cha\^{i}nes de Markov Constructives Index\'{e}es par Z

Author(s): Jean Brossard and Christophe Leuridan

Abstract: Nous \'{e}tudions les cha\^{{\i}}nes de Markov $(X_n)_{n\in\mathbf {Z}}$ gouvern\'{e}es par une relation de r\'{e}currence de la forme $X_{n+1}=f(X_n,V_{n+1})$, o\`{u} $(V_n)_{n\in\mathbf{Z}}$ est une suite de variables al\'{e}atoires ind\'{e}pendantes et de m\^{e}me loi telle pour tout $n\in \mathbf{Z}$, $V_{n+1}$ est ind\'{e}pendante de la suite $((X_k,V_k))_{k\le n}$. L'objet de l'article est de donner une condition n\'{e}cessaire et suffisante pour que les innovations $(V_n)_{n\in \mathbf{Z}}$ d\'{e}terminent compl\`{e}tement la suite $(X_n)_{n\in \mathbf{Z}}$ et de d\'{e}crire l'information manquante dans le cas contraire.

http://arxiv.org/abs/0707.3860

5866. The Jancovici - Lebowitz - Magnificat law for large fluctuations of random complex zeroes

Author(s): F. Nazarov and M. Sodin and A. Volberg

Abstract: By random complex zeroes we mean the zero set of a random entire function whose Taylor coefficients are independent complex-valued Gaussian variables, and the variance of the k-th coefficient is 1/k!. This zero set is distribution invariant with respect to isometries of the complex plane. We study large fluctuations of random complex zeroes and show that they obey the asymptotic law that was discovered some time ago by Jancovici, Lebowitz and Magnificat for charge fluctuations of a Coulomb system of particles.

http://arxiv.org/abs/0707.3863

5867. Filtration shrinkage by level-crossings of a diffusion

Author(s): A. Deniz Sezer

Abstract: We develop the mathematics of a filtration shrinkage model that has recently been considered in the credit risk modeling literature. Given a finite collection of points $x_1<...

http://arxiv.org/abs/0707.3866

5868. The growth of additive processes

Author(s): Ming Yang

Abstract: Let $X_t$ be any additive process in $\mathbb{R}^d.$ There are finite indices $\delta_i, \beta_i, i=1,2$ and a function $u$, all of which are defined in terms of the characteristics of $X_t$, such that \liminf_{t\to0}u(t)^{-1/\eta}X_t^*= \cases{0, \quad if $\eta> \delta_1$, \cr\infty, \quad if $\eta<\delta_2$,} \limsup_{t\to0}u(t)^{-1/\eta}X_t^*= \cases{0, \quad if $\eta> \beta_2$, \cr\infty, \quad if $\eta<\beta_1$,}\qquad {a.s.}, where $X_t^*=\sup_{0\le s\le t}|X_s|.$ When $X_t$ is a L\'{e}vy process with $X_0=0$, $\delta_1=\delta_2$, $\beta_1=\beta_2$ and $u(t)=t.$ This is a special case obtained by Pruitt. When $X_t$ is not a L\'{e}vy process, its characteristics are complicated functions of $t$. However, there are interesting conditions under which $u$ becomes sharp to achieve $\delta_1=\delta_2$, $\beta_1=\beta_2.$

http://arxiv.org/abs/0707.3886

5869. Maximal Arithmetic Progressions in Random Subsets

Author(s): Itai Benjamini and Ariel Yadin and Ofer Zeitouni

Abstract: Let U(N) denote the maximal length of arithmetic progressions in a random uniform subset of {0,1}^N. By an application of the Chen-Stein method, we show that U(N)- 2 log(N)/log(2) converges in law to an extreme type (asymmetric) distribution. The same result holds for the maximal length W(N) of arithmetic progressions (mod N). When considered in the natural way on a common probability space, we observe that U(N)/log(N) converges almost surely to 2/log(2), while W(N)/log(N) does not converge almost surely (and in particular, limsup W(N)/log(N) is at least 3/log(2)).

http://arxiv.org/abs/0707.3888

5870. Multivariate normal approximation in geometric probability

Author(s): Mathew D. Penrose and Andrew R. Wade

Abstract: Consider a measure $\mu_\lambda = \sum_x \xi_x \delta_x$ where the sum is over points $x$ of a Poisson point process of intensity $\lambda$ on a bounded region in $d$-space, and $\xi_x$ is a functional determined by the Poisson points near to $x$, i.e. satisfying an exponential stabilization condition, along with a moments condition (examples include statistics for proximity graphs, germ-grain models and random sequential deposition models). A known general result says the $\mu_\lambda$-measures (suitably scaled and centred) of disjoint sets in $R^d$ are asymptotically independent normals as $ \lambda \to \infty$; here we give an $O(\lambda^{-1/(2d + \epsilon)})$ bound on the rate of convergence. We illustrate our result with an explicit multivariate central limit theorem for the nearest-neighbour graph on Poisson points on a finite collection of disjoint intervals.

http://arxiv.org/abs/0707.3898

5871. Non normal CLTs for functions of the increments of Gaussian processes with convex increment's variance

Author(s): Michael Marcus and Jay Rosen

Abstract: Let G be a mean zero Gaussian processes with stationary increments and set \si ^2(|x-y|)= E(G(x)-G(y))^2. Let f be a function with Ef^{2}(\eta)< \ff, where \eta=N(0,1). When \si^2 is convex and regularly varying at zero and \lim_{h\to 0} \si(h)/h=\ff \quad {but} \quad ({d\over ds^2}\si^2(s))^{j_0} \mbox{is locally integrable} for some integer j_0\ge 1, and satisfies some additional regularity conditions, then \int_a^bf(\frac{G(x+h)-G(x)}{\si (h)}) dx = \sum_{j=0}^{j_0} (h/\si(h))^{j} {E(H_{j}(\eta) f(\eta))\over\sqrt {j!}} :(G')^{j}:(I_{[a,b]}) +o({h\over\si (h)})^{j_0}\nn in L^2. Here H_j is the j-th Hermite polynomial in the Hermite polynomial expansion of f. Also :(G')^{j}:(I_{[a,b]}) is a j-th order Wick power Gaussian chaos constructed from the Gaussian field G'(g)=\int g(x) dG(x) with covariance E(G'(g)G'(\wt g)) = \int \int \rho (x-y)g(x)\wt g(y) dx dy where \rho(s)={1/2}{d^{2}\over ds^2}\si^2(s). Moreover, under the same conditions \lim_{h\downarrow0}\int_a^b :(\frac{G(x+h)-G(x)}{h})^{j_0}: dx = :(G')^{j_0}:(I_{[a,b]}) \qquad {a.s.}

http://arxiv.org/abs/0707.3928

5872. Mixed States Markov Random Fields with Symbolic Labels and Multidimensional Real Values

Author(s): Bruno Cernuschi-Frias (IRISA)

Abstract: New theoretical results are presented here on the recently introduced model called mixed states MRF. Such models were introduced in the context of image motion analysis and are useful to represent information which can take both discrete values accounting for symbolic states, and real values corresponding to continuous measurements. In particular, results are given when the global energy for the Gibbs formulation expressing the mixed states model, can be decomposed into one term accounting for the discrete part of the model, and a second term related to the continuous part. This decomposition theorem permits to define conditional mixed states models in a very simple way.

http://arxiv.org/abs/0707.3986

5873. Regularly varying multivariate time series

Author(s): Bojan Basrak and Johan Segers

Abstract: A multivariate, stationary time series is said to be jointly regularly varying if all its finite-dimensional distributions are multivariate regularly varying. This property is shown to be equivalent to weak convergence of the conditional distribution of the rescaled series given that, at a fixed time instant, its distance to the origin exceeds a threshold tending to infinity. The limit object, called the tail process, admits a decomposition in independent radial and angular components. Under an appropriate mixing condition, this tail process allows for a concise and explicit description of the limit of a sequence of point processes recording both the times and the positions of the time series when it is far away from the origin. The theory is applied to multivariate moving averages of finite order with random coefficient matrices.

http://arxiv.org/abs/0707.3989

5874. Correlation Inequalities for Generalized Potts Model: General Griffiths' Inequalities

Author(s): Nasir Ganikhodjaev and Fatimah Abdul Razak

Abstract: In this paper, correlation inequalities which have been considered on Ising model are extended to q-Potts model. It is considered on generalized Potts model with interaction of any number of spins. We replace the set of spin values $F=\{1,2,..., q\}$ by the centered set $F=\{-(q-1)/2,-(q-3)/2,... ,(q-3)/2,(q-1)/2\}$. Let $N$ be the subset of one-dimensional lattice with $n$ vertices, $\g=(\s_1,\s_2,...,\s_n):N \to F^c$ be a configuration where ${(\s_i)}_\g$ is the number which appears as the ith spin (component) in $\g$ and $\s_i$ be a random variable whose value at $\g$ is ${(\s_i)}_\g$. Define $\s^R=\prod_{i \in R}\s_i$ for any list $R$ where any $i \in R$ implies that $i \in N$. We first prove that $<\s^R > \ge 0$ then we prove that for any two lists $R$ and $S$, we have $<\s^R \s^S >- < \s^R > < \s^S > \ge 0$.

http://arxiv.org/abs/0707.3848

5875. The passage time distribution for a birth-and-death chain: Strong stationary duality gives a first stochastic proof

Author(s): James Allen Fill

Abstract: A well-known theorem usually attributed to Keilson states that, for an irreducible continuous-time birth-and-death chain on the nonnegative integers and any d, the passage time from state 0 to state d is distributed as a sum of d independent exponential random variables. Until now, no probabilistic proof of the theorem has been known. In this paper we use the theory of strong stationary duality to give a stochastic proof of a similar result for discrete-time birth-and-death chains and geometric random variables, and the continuous-time result (which can also be given a direct stochastic proof) then follows immediately. In both cases we link the parameters of the distributions to eigenvalue information about the chain. Intimately related to the passage-time theorem is a theorem of Fill that any fastest strong stationary time T for an ergodic birth-and-death chain on {0, > ..., d} in continuous time with generator G, started in state 0, is distributed as a sum of d independent exponential random variables whose rate parameters are the nonzero eigenvalues of the negative of G. Our approach yields the first (sample-path) construction of such a T for which individual such exponentials summing to T can be explicitly identified.

http://arxiv.org/abs/0707.4042

5876. Characterizations of probability distributions via bivariate regression of record values

Author(s): George P. Yanev and M. Ahsanullah and and M.I. Beg

Abstract: Bairamov et al. (Aust N Z J Stat 47:543-547, 2005) characterize the exponential distribution in terms of the regression of a function of a record value with its adjacent record values as covariates. We extend these results to the case of non-adjacent covariates. We also consider a more general setting involving monotone transformations. As special cases, we present characterizations involving weighted arithmetic, geometric, and harmonic means.

http://arxiv.org/abs/0707.4121

5877. Large time asymptotics of growth models on space-like paths I: PushASEP

Author(s): Alexei Borodin (1) and Patrik L. Ferrari (2) ((1) Caltech and (2) WIAS Berlin)

Abstract: We consider a new interacting particle system on the one- dimensional lattice that interpolates between TASEP and Toom's model: A particle cannot jump to the right if the neighboring site is occupied, and when jumping to the left it simply pushes all the neighbors that block its way. We prove that for flat and step initial conditions, the large time fluctuations of the height function of the associated growth model along any space-like path are described by the Airy_1 and Airy_2 processes. This includes fluctuations of the height profile for a fixed time and fluctuations of a tagged particle's trajectory as special cases.

http://arxiv.org/abs/0707.2813

5878. Multiclass Hammersley-Aldous-Diaconis process and multiclass- customer queues

Author(s): Pablo A. Ferrari and James B. Martin

Abstract: In the Hammersley-Aldous-Diaconis process infinitely many particles sit in R and at most one particle is allowed at each position. A particle at x $ whose nearest neighbor to the right is at y, jumps at rate y-x to a position uniformly distributed in the interval (x,y). The basic coupling between trajectories with different initial configuration induces a process with different classes of particles. We show that the invariant measures for the two-class process can be obtained as follows. First, a stationary M/M/ 1 queue is constructed as a function of two homogeneous Poisson processes, the arrivals with rate \lambda and the (attempted) services with rate \rho> \lambda. Then put the first class particles at the instants of departures (effective services) and second class particles at the instants of unused services. The procedure is generalized for the n-class case by using n-1 queues in tandem with n-1 priority-types of customers. A multi-line process is introduced; it consists of a coupling (different from Liggett's basic coupling), having as invariant measure the product of Poisson processes. The definition of the multi- line process involves the dual points of the space-time Poisson process used in the graphical construction of the system. The coupled process is a transformation of the multi-line process and its invariant measure the transformation described above of the product measure.

http://arxiv.org/abs/0707.4202

5879. Ergodic BSDEs and Optimal Ergodic Control in Banach Spaces

Author(s): Marco Fuhrman (Dipartimento Di Matematica) and Ying Hu (IRMAR) and Gianmario Tessitore (Dipartimento Di Matematica E Applicazioni)

Abstract: In this paper we introduce a new kind of Backward Stochastic Differential Equations, called ergodic BSDEs, which arise naturally in the study of optimal ergodic control. We study the existence, uniqueness and regularity of solution to ergodic BSDEs. Then we apply these results to the optimal ergodic control of a Banach valued stochastic state equation. We also establish the link between the ergodic BSDEs and the associated Hamilton-Jacobi-Bellman equation. Applications are given to ergodic control of stochastic partial differential equations.

http://arxiv.org/abs/0707.4214

5880. A convexity property of expectations under exponential weights

Author(s): Marton Balazs and Timo Seppalainen

Abstract: Take a random variable X with some finite exponential moments. Define an exponentially weighted expectation by E^t(f) = E(e^{tX}f)/E(e^{tX}) for admissible values of the parameter t. Denote the weighted expectation of X itself by r(t) = E^t(X), with inverse function t(r). We prove that for a convex function f the expectation E^{t(r)}(f) is a convex function of the parameter r. Along the way we develop correlation inequalities for convex functions. Motivation for this result comes from equilibrium investigations of some stochastic interacting systems with stationary product distributions. In particular, convexity of the hydrodynamic flux function follows in some cases.

http://arxiv.org/abs/0707.4273

5881. Neumann Heat kernel monotonicity

Author(s): R. Ba\~nuelos and T. Kulczycki and B. Siudeja

Abstract: We prove that the diagonal of the transition probabilities for the d-dimensional Bessel processes on (0, 1], reflected at 1, which we denote by $p_R^N(t, r,r)$, is an increasing function of r for d>2 and that this is false for d=2.

http://arxiv.org/abs/0707.4299

5882. Moderate deviations and laws of the iterated logarithm for the local times of additive L\'{e}vy processes and additive random walks

Author(s): Xia Chen

Abstract: We study the upper tail behaviors of the local times of the additive L\'{e}vy processes and additive random walks. The limit forms we establish are the moderate deviations and the laws of the iterated logarithm for the L_2-norms of the local times and for the local times at a fixed site.

http://arxiv.org/abs/0707.4355

5883. Exact Hausdorff measure on the boundary of a Galton--Watson tree

Author(s): Toshiro Watanabe

Abstract: A necessary and sufficient condition for the almost sure existence of an absolutely continuous (with respect to the branching measure) exact Hausdorff measure on the boundary of a Galton--Watson tree is obtained. In the case where the absolutely continuous exact Hausdorff measure does not exist almost surely, a criterion which classifies gauge functions $\phi$ according to whether $\phi$-Hausdorff measure of the boundary minus a certain exceptional set is zero or infinity is given. Important examples are discussed in four additional theorems. In particular, Hawkes's conjecture in 1981 is solved. Problems of determining the exact local dimension of the branching measure at a typical point of the boundary are also solved.

http://arxiv.org/abs/0707.4358

5884. Backward stochastic differential equations with random stopping time and singular final condition

Author(s): A. Popier

Abstract: In this paper we are concerned with one-dimensional backward stochastic differential equations (BSDE in short) of the following type: \[Y_t=\xi -\int_{t\wedge \tau}^{\tau}Y_r|Y_r|^q dr-\int_{t\wedge \tau}^{\tau}Z_r dB_r,\qquad t\geq 0,\] where $\tau$ is a stopping time, $q$ is a positive constant and $\xi$ is a $\mathcal{F}_{\tau}$-measurable random variable such that $\mathbf{P}(\xi =+\infty)>0$. We study the link between these BSDE and the Dirichlet problem on a domain $D\subset \mathbb{R}^d$ and with boundary condition $g$, with $g=+\infty$ on a set of positive Lebesgue measure. We also extend our results for more general BSDE.

http://arxiv.org/abs/0707.4387

5885. Large Deviations for Occupation Times of Markov Processes with L_2 Semigroups

Author(s): N. Jain and N.V. Krylov

Abstract: Our aim is to unify and extend the large deviation upper and lower bounds for the empiricals of a Markov process with L_2 semigroups under minimal conditions on the state space and the process trajectories; for example, no strong Markov property is needed. The methods used here apply in both continuous and discrete time. We present the proofs for continuous time only because of the inherent technical difficulties in that situation; the proofs can be adapted for discrete time in a straightforward manner.

http://arxiv.org/abs/0707.4469

5886. Trace Estimates for Stable Processes

Author(s): Rodrigo Banuelos and Tadeusz Kulczycki

Abstract: In this paper we study the behaviour in time of the trace (the partition function) of the heat semigroup associated with symmetric stable processes in domains of $\Rd$. In particular, we show that for domains with the so called {\it{$R$-smoothness}} property the second terms in the asymptotic as $t\to 0$ involves the surface area of the domain, just as in the case of Brownian motion.

http://arxiv.org/abs/0707.4313

5887. Non-equilibrium scaling limit for a tagged particle in the simple exclusion process with long jumps

Author(s): Milton D. Jara

Abstract: We prove an invariance principle for a tagged particle in a simple exclusion process out of equilibrium. The scaling limit is a time-inhomogeneous process of independent increments, related to the solution of a fractional heat equation.

http://arxiv.org/abs/0707.4491

5888. On the paper ``Weak convergence of some classes of martingales with jumps''

Author(s): Yoichi Nishiyama

Abstract: This note extends some results of Nishiyama [Ann. Probab. 28 (2000) 685--712]. A maximal inequality for stochastic integrals with respect to integer-valued random measures which may have infinitely many jumps on compact time intervals is given. By using it, a tightness criterion is obtained; if the so-called quadratic modulus is bounded in probability and if a certain entropy condition on the parameter space is satisfied, then the tightness follows. Our approach is based on the entropy techniques developed in the modern theory of empirical processes.

http://arxiv.org/abs/0707.4536

5889. Structural properties of proportional fairness: stability and insensitivity

Author(s): Laurent Massouli\'e

Abstract: In this article we provide a novel characterization of the proportionally fair bandwidth allocation of network capacities, in terms of the Fenchel--Legendre transform of the network capacity region. We use this characterization to prove stability (i.e., ergodicity) of network dynamics under proportionally fair sharing, by exhibiting a suitable Lyapunov function. Our stability result extends previously known results to a more general model including Markovian users routing. In particular, it implies that the stability condition previously known under exponential service time distributions remains valid under so-called phase-type service time distributions. We then exhibit a modification of proportional fairness, which coincides with it in some asymptotic sense, is reversible (and thus insensitive), and has explicit stationary distribution. Finally we show that the stationary distributions under modified proportional fairness and balanced fairness, a sharing criterion proposed because of its insensitivity properties, admit the same large deviations characteristics. These results show that proportional fairness is an attractive bandwidth allocation criterion, combining the desirable properties of ease of implementation with performance and insensitivity.

http://arxiv.org/abs/0707.4542

5890. Good rough path sequences and applications to anticipating stochastic calculus

Author(s): Laure Coutin and Peter Friz and Nicolas Victoir

Abstract: We consider anticipative Stratonovich stochastic differential equations driven by some stochastic process lifted to a rough path. Neither adaptedness of initial point and vector fields nor commuting conditions between vector field is assumed. Under a simple condition on the stochastic process, we show that the unique solution of the above SDE understood in the rough path sense is actually a Stratonovich solution. We then show that this condition is satisfied by the Brownian motion. As application, we obtain rather flexible results such as support theorems, large deviation principles and Wong--Zakai approximations for SDEs driven by Brownian motion along anticipating vectorfields. In particular, this unifies many results on anticipative SDEs.

http://arxiv.org/abs/0707.4546

5891. Central limit theorem and almost sure central limit theorem for the product of some partial sums

Author(s): Yu Miao

Abstract: In this paper, we give the central limit theorem and almost sure central limit theorem for products of some partial sums of independent identically distributed random variables.

http://arxiv.org/abs/0707.4549

5892. Stationary distributions of a model of sympatric speciation

Author(s): Feng Yu

Abstract: This paper deals with a model of sympatric speciation, that is, speciation in the absence of geographical separation, originally proposed by U. Dieckmann and M. Doebeli in 1999. We modify their original model to obtain a Fleming--Viot type model and study its stationary distribution. We show that speciation may occur, that is, the stationary distribution puts most of the mass on a configuration that does not concentrate on the phenotype with maximum carrying capacity, if competition between phenotypes is intense enough. Conversely, if competition between phenotypes is not intense, then speciation will not occur and most of the population will have the phenotype with the highest carrying capacity. The length of time it takes speciation to occur also has a delicate dependence on the mutation parameter, and the exact shape of the carrying capacity function and the competition kernel.

http://arxiv.org/abs/0707.4553

5893. Probabilistic validation of homology computations for nodal domains

Author(s): Konstantin Mischaikow and Thomas Wanner

Abstract: Homology has long been accepted as an important computable tool for quantifying complex structures. In many applications, these structures arise as nodal domains of real-valued functions and are therefore amenable only to a numerical study based on suitable discretizations. Such an approach immediately raises the question of how accurate the resulting homology computations are. In this paper, we present a probabilistic approach to quantifying the validity of homology computations for nodal domains of random fields in one and two space dimensions, which furnishes explicit probabilistic a priori bounds for the suitability of certain discretization sizes. We illustrate our results for the special cases of random periodic fields and random trigonometric polynomials.

http://arxiv.org/abs/0707.4588

5894. Uniform convergence of exact large deviations for renewal reward processes

Author(s): Zhiyi Chi

Abstract: Let (X_n,Y_n) be i.i.d. random vectors. Let W(x) be the partial sum of Y_n just before that of X_n exceeds x>0. Motivated by stochastic models for neural activity, uniform convergence of the form $\sup_{c\in I}|a(c,x) \operatorname {Pr}\{W(x)\gecx\}-1|=o(1)$, $x\to\infty$, is established for probabilities of large deviations, with a(c,x) a deterministic function and I an open interval. To obtain this uniform exact large deviations principle (LDP), we first establish the exponentially fast uniform convergence of a family of renewal measures and then apply it to appropriately tilted distributions of X_n and the moment generating function of W(x). The uniform exact LDP is obtained for cases where X_n has a subcomponent with a smooth density and Y_n is not a linear transform of X_n. An extension is also made to the partial sum at the first exceedance time.

http://arxiv.org/abs/0707.4596

5895. Heavy traffic limit for a processor sharing queue with soft deadlines

Author(s): H. Christian Gromoll and {\L}ukasz Kruk

Abstract: This paper considers a GI/GI/1 processor sharing queue in which jobs have soft deadlines. At each point in time, the collection of residual service times and deadlines is modeled using a random counting measure on the right half-plane. The limit of this measure valued process is obtained under diffusion scaling and heavy traffic conditions and is characterized as a deterministic function of the limiting queue length process. As special cases, one obtains diffusion approximations for the lead time profile and the profile of times in queue. One also obtains a snapshot principle for sojourn times.

http://arxiv.org/abs/0707.4600

5896. Large time asymptotics of growth models on space-like paths

Author(s): Alexei Borodin and Patrik L. Ferrari and Tomohiro Sasamoto

Abstract: We consider the polynuclear growth (PNG) model in 1+1 dimension with flat initial condition and no extra constraints. The joint distributions of surface height at finitely many points at a fixed time moment are given as marginals of a signed determinantal point process. The long time scaling limit of the surface height is shown to coincide with the Airy_1 process. This result holds more generally for the observation points located along any space- like path in the space-time plane. We also obtain the corresponding results for the discrete time TASEP (totally asymmetric simple exclusion process) with parallel update.

http://arxiv.org/abs/0707.4207

5897. The alternating marked point process of h-slopes of the drifted Brownian motion

Author(s): A. Faggionato

Abstract: We show that the slopes between h-extrema of the drifted 1D Brownian motion form a stationary alternating marked point process, extending the result of J. Neveu and J. Pitman for the non drifted case. Our analysis covers the results on the statistics of h-extrema obtained by P. Le Doussal, C. Monthus and D. Fisher via a Renormalization Group analysis and gives a complete description of the slope between h-extrema covering the origin by means of the Palm-- Khinchin theory. Moreover, we analyze the behavior of the Brownian motion near its h-extrema.

http://arxiv.org/abs/0708.0128

5898. Self-similar branching Markov chains

Author(s): Nathalie Krell (PMA)

Abstract: The main purpose of this work is to study self-similar branching Markov chains. First we will construct such a process. Then we will establish certain Limit Theorems using the theory of self-similar Markov processes.

http://arxiv.org/abs/0708.0138

5899. Data-driven goodness-of-fit tests

Author(s): Mikhail Langovoy

Abstract: A general method for constructing tests of statistical hypotheses is proposed. The method offers a generalization of the theory of score tests. Our tests are incorporated with model selection rules to choose reasonable model dimensions automatically by the data. A unified approach for proving consistency of the tests is developed.

http://arxiv.org/abs/0708.0169

5900. Towards conformal invariance of 2D lattice models

Author(s): Stanislav Smirnov

Abstract: Many 2D lattice models of physical phenomena are conjectured to have conformally invariant scaling limits: percolation, Ising model, self- avoiding polymers, ... This has led to numerous exact (but non-rigorous) predictions of their scaling exponents and dimensions. We will discuss how to prove the conformal invariance conjectures, especially in relation to Schramm- Loewner Evolution.

http://arxiv.org/abs/0708.0032

5901. A new formulation of asset trading games in continuous time with essential forcing of variation exponent

Author(s): Kei Takeuchi and Masayuki Kumon and Akimichi Takemura

Abstract: We introduce a new formulation of asset trading games in continuous time in the framework of the game-theoretic probability established by Shafer and Vovk (2001). In our formulation, the market moves continuously but an investor trades in discrete times, which can depend on the past path of the market. We prove that an investor can essentially force that the asset price path behaves with the variation exponent exactly equal to two. Our proof is based on embedding high-frequency discrete time games into the continuous time game and the use of the Bayesian strategy of Kumon, Takemura and Takeuchi (2007b) for discrete time coin-tossing games. We also clarify that the main growth part of the investor's capital processes is lucidly described by the information quantities, which are derived from the Kullback-Leibler information with respect to the empirical fluctuation of the asset price.

http://arxiv.org/abs/0708.0275

5902. The Central Limit Theorem for the Smoluchovski Coagulation Model

Author(s): Vassili Kolokoltsov

Abstract: The general model of coagulation is considered. For basic classes of unbounded coagulation kernels the central limit theorem (CLT) is obtained for the fluctuations around the dynamic law of large numbers (LLN). A rather precise rate of convergence is given both for LLN and CLT.

http://arxiv.org/abs/0708.0329

5903. Propagation of Fluctuations in Biochemical Systems, II: Nonlinear Chains

Author(s): David F. Anderson and Jonathan C. Mattingly

Abstract: We consider biochemical reaction chains and investigate how random external fluctuations, as characterized by variance and coefficient of variation, propagate down the chains. We perform such a study under the assumption that the number of molecules is high enough so that the behavior of the concentrations of the system is well approximated by differential equations. We conclude that the variances and coefficients of variation of the fluxes will decrease as one moves down the chain and, through an example, show that there is no corresponding result for the variances of the chemical species. We also prove that the fluctuations of the fluxes as characterized by their time averages decrease down reaction chains. The results presented give insight into how biochemical reaction systems are buffered against external perturbations solely by their underlying graphical structure and point out the benefits of studying the out-of-equilibrium dynamics of systems.

http://arxiv.org/abs/0708.0380

5904. Multisource Bayesian change detection

Author(s): Savas Dayanik and Harold Vincent Poor and Semih Onur Sezer

Abstract: Suppose that local characteristics of several independent compound Poisson and Wiener processes change suddenly and simultaneously at some unobservable disorder time. The problem is to detect the disorder time as quickly as possible after it happens and minimize the rate of false alarms at the same time. These problems arise, for example, from managing product quality in manufacturing systems and preventing the spread of infectious diseases. The promptness and accuracy of detection rules improve greatly if multiple independent information sources are available. Earlier work on sequential change detection in continuous time does not provide optimal rules for situations in which several marked count data and continuously changing signals are simultaneously observable. In this paper, optimal Bayesian sequential detection rules are developed for such problems when the marked count data is in the form of independent compound Poisson processes, and the continuously changing signals form a multi-dimensional Wiener process. An auxiliary optimal stopping problem for a jump-diffusion process is solved by transforming it first into a sequence of optimal stopping problems for a pure diffusion by means of a jump operator. This method is new and can be very useful in other applications as well, because it allows the use of the powerful optimal stopping theory for diffusions.

http://arxiv.org/abs/0708.0224

5905. Introducing a Probabilistic Structure on Sequential Dynamical Systems, Simulation and Reduction of Probabilistic Sequential Networks

Author(s): Maria A. Avino-Diaz

Abstract: A probabilistic structure on sequential dynamical systems is introduced here, the new model will be called Probabilistic Sequential Network, PSN. The morphisms of Probabilistic Sequential Networks are defined using two algebraic conditions, whose imply that the distribution of probabilities in the systems are close. It is proved here that two homomorphic Probabilistic Sequential Networks have the same equilibrium or steady state probabilities. Additionally, the proof of the set of PSN with its morphisms form the category PSN, having the category of sequential dynamical systems SDS, as a full subcategory is given. Several examples of morphisms, subsystems and simulations are given.

http://arxiv.org/abs/0707.0026

5906. On representing claims for coherent risk measures

Author(s): Saul Jacka and Abdelkarem Berkaoui

Abstract: We consider the problem of representing claims for coherent risk measures. For this purpose we introduce the concept of (weak and strong) time- consistency with respect to a portfolio of assets, generalizing the one defined by Delbaen. In a similar way we extend the notion of m-stability, by introducing weak and strong versions. We then prove that the two concepts of m-stability and time-consistency are still equivalent, thus giving necessary and sufficient conditions for a coherent risk measure to be represented by a market with proportional transaction costs. We go on to deduce that, under a separability assumption, any coherent risk measure is strongly time-consistent with respect to a suitably chosen countable portfolio, and show the converse: that any market with proportional transaction costs is equivalent to a market priced by a coherent risk measure, essentially establishing the equivalence of the two concepts.

http://arxiv.org/abs/0708.0512

5907. Edge Flows in the Complete Random-Lengths Network

Author(s): David J. Aldous and Shankar Bhamidi

Abstract: Consider the complete n-vertex graph whose edge-lengths are independent exponentially distributed random variables. Simultaneously for each pair of vertices, put a constant flow between them along the shortest path. Each edge gets some random total flow. In the $n \to \infty$ limit we find explicitly the empirical distribution of these edge-flows, suitably normalized.

http://arxiv.org/abs/0708.0555

5908. Probabilistic implications of symmetries of q-Hermite and Al-Salam-Chihara polynomials

Author(s): Pawe{\l} J. Szab{\l}owski

Abstract: First we generalize to $q-$series case, a well known formula $(x+y) ^{n}% =\sum_{i=0}^{n}\binom{n}{k}i^{k}H_{n-k}(x) H_{k}(-iy) ,$ where H_{k} (x) denotes k-th Hermite polynomial. Then we apply this generalization to Al- Salam-Chihara polynomials for specific values of parameters. We use this result to prove the existence of stationary random fields with linear regressions and thus close an open question posed by W. Bryc et al.. We prove this result by describing a discrete 1 dimensional conditional distribution. Its support consist of zeros of certain Al-Salam-Chihara polynomials.

http://arxiv.org/abs/0708.0563

5909. Avoiding small subgraphs in Achlioptas processes

Author(s): Michael Krivelevich and Po-Shen Loh and Benny Sudakov

Abstract: For a fixed integer r, consider the following random process. At each round, one is presented with r random edges from the edge set of the complete graph on n vertices, and is asked to choose one of them. The selected edges are collected into a graph, which thus grows at the rate of one edge per round. This is a natural generalization of what is known in the literature as an Achlioptas process (the original version has r=2), which has been studied by many researchers, mainly in the context of delaying or accelerating the appearance of the giant component. In this paper, we investigate the small subgraph problem for Achlioptas processes. That is, given a fixed graph H, we study whether there is a deterministic online algorithm that substantially delays or accelerates a typical appearance of H, compared to its threshold of appearance in the random graph G(n, M). It is easy to see that one cannot accelerate the appearance of any fixed graph by more than the constant factor r, so we concentrate on the task of avoiding H. We determine thresholds for the avoidance of all cycles C_t, cliques K_t, and complete bipartite graphs K_{t,t}, in every Achlioptas process with parameter r >= 2.

http://arxiv.org/abs/0708.0443

5910. New Dirichlet Mean Identities

Author(s): Lancelot F. James

Abstract: An important line of research is the investigation of the laws of random variables known as Dirichlet means as discussed in Cifarelli and Regazzini(1990). However there is not much information on inter- relationships between different Dirichlet means. Here we introduce two distributional operations, which consist of multiplying a mean functional by an independent beta random variable and an operation involving an exponential change of measure. These operations identify relationships between different means and their densities. This allows one to use the often considerable analytic work to obtain results for one Dirichlet mean to obtain results for an entire family of otherwise seemingly unrelated Dirichlet means. Additionally, it allows one to obtain explicit densities for the related class of random variables that have generalized gamma convolution distributions, and the finite-dimensional distribution of their associated L\'evy processes. This has implications in, for instance, the explicit description of Bayesian nonparametric prior and posterior models, and more generally in a variety of applications in probability and statistics involving Levy processes.

http://arxiv.org/abs/0708.0614

5911. Lamperti Type Laws: Positive Linnik, Bessel Bridge Occupation and Mittag-Leffler Functions

Author(s): Lancelot F. James

Abstract: This paper obtains density and cdf formula, and various distributional identities, for random variables defined as the ratio of two independent positive random variables where one variable has an $\alpha$ stable law, for $0<\alpha<1,$ and the other variable has the law defined by power tempering the density of an $\alpha$ stable random variable by a factor $\theta>- \alpha$. When $\theta=0$, these variables equate with the ratio investigated by Lamperti which remarkably was shown to have a simple density. This variable arises in a variety of areas and gains importance from a close connection to the stable laws. This rationale motivates the investigations of its generalizations which we refer to as Lamperti type laws. Here specifically the results are used to obtain results for 3 interesting quantities, which appear in a variety of contexts. Explicit distributional formulae and identities are derived for the class of positive generalized Linnik random variables. Then the best known results for the density of the time spent positive of a Bessel bridge of dimension $2-2\alpha$, and related quantities, are obtained. Additionally, integral representations and other identities for a class of generalized Mittag-Leffler functions are obtained. We will also describe the connections between these results and show how they generalize previous results in the literature.

http://arxiv.org/abs/0708.0618

5912. Gibbs Partitions (EPPF's) Derived From a Stable Subordinator are Fox H and Meijer G Transforms

Author(s): Man-Wai Ho and Lancelot F. James and and John W. Lau

Abstract: This paper derives explicit results for the infinite Gibbs partitions generated by the jumps of an $\alpha-$stable subordinator, derived in Pitman \cite{Pit02, Pit06}. We first show that for general $\alpha$ the conditional EPPF can be represented as ratios of Fox-$H$ functions, and in the case of rational $\alpha,$ Meijer-G functions. Furthermore the results show that the resulting unconditional EPPF's, can be expressed in terms of H and G transforms indexed by a function h. Hence when h is itself a H or G function the EPPF is also an H or G function. An implication, in the case of rational $ \alpha,$ is that one can compute explicitly thousands of EPPF's derived from possibly exotic special functions. This would also apply to all $\alpha$ except that computations for general Fox functions are not yet available. However, moving away from special functions, we demonstrate how results from probability theory may be used to obtain calculations. We show that a forward recursion can be applied that only requires calculation of the simplest components. Additionally we identify general classes of EPPF's where explicit calculations can be carried out using distribution theory.

http://arxiv.org/abs/0708.0619

5913. Quenched Limits for Transient, Ballistic, Sub-Gaussian One- Dimensional Random Walk in Random Environment

Author(s): Jonathon Peterson

Abstract: We consider a nearest-neighbor, one-dimensional random walk $\{X_n \}_{n\geq 0}$ in a random i.i.d. environment, in the regime where the walk is transient with speed v_P > 0 and there exists an $s\in(1,2)$ such that the annealed law of $n^{-1/s} (X_n - n v_P)$ converges to a stable law of parameter s. Under the quenched law (i.e., conditioned on the environment), we show that no limit laws are possible. In particular we show that there exist sequences {t_k} and {t_k'} depending on the environment only, such that a quenched central limit theorem holds along the subsequence t_k, but the quenched limiting distribution along the subsequence t_k' is a centered reverse exponential distribution. This complements the results of a recent paper of Peterson and Zeitouni (arXiv:0704.1778v1 [math.PR]) which handled the case when the parameter $s\in(0,1)$.

http://arxiv.org/abs/0708.0649

5914. Second Order Cumulants of products

Author(s): James A. Mingo (Queen's University) and Roland Speicher (Queen's University), Edward Tan (Queen's University)

Abstract: We derive a formula which expresses a second order cumulant whose entries are products as a sum of cumulants where the entries are single factors. This extends to the second order case the formula of Krawczyk and Speicher. We apply our result to the problem of calculating the second order cumulants of a semi-circular and Haar unitary operator.

http://arxiv.org/abs/0708.0586

5915. Investment and Consumption without Commitment

Author(s): Ivar Ekeland and Traian A. Pirvu

Abstract: In this paper, we investigate the Merton portfolio management problem in the context of non-exponential discounting. This gives rise to time- inconsistency of the decision-maker. If the decision-maker at time t=0 can commit his/her successors, he/she can choose the policy that is optimal from his/her point of view, and constrain the others to abide by it, although they do not see it as optimal for them. If there is no commitment mechanism, one must seek a subgame-perfect equilibrium strategy between the successive decision- makers. In the line of the earlier work by Ekeland and Lazrak we give a precise definition of equilibrium strategies in the context of the portfolio management problem, with finite horizon, we characterize it by a system of partial differential equations, and we show existence in the case when the utility is CRRA and the terminal time T is small. We also investigate the infinite-horizon case and we give two different explicit solutions in the case when the utility is CRRA (in contrast with the case of exponential discount, where there is only one). Some of our results are proved under the assumption that the discount function h(t) is a linear combination of two exponentials, or is the product of an exponential by a linear function.

http://arxiv.org/abs/0708.0588

5916. The effect of memory on functional large deviations of infinite moving average processes

Author(s): Souvik Ghosh and Gennady Samorodnitsky

Abstract: The large deviations of an infinite moving average process with exponentially light tails are very similar to those of an i.i.d. sequence as long as the coefficients decay fast enough. If they do not, the large deviations change dramatically. We study this phenomenon in the context of functional large, moderate and huge deviation principles.

http://arxiv.org/abs/0708.0865

5917. Pricing, Hedging and Optimally Designing Derivatives Via Minimization of Risk Measures

Author(s): Pauline Barrieu (1) and Nicole El Karoui (2) ((1) and Statistics department, London School of Economics, UK, (2) CMAP, Ecole Polytechnique, France)

Abstract: The question of pricing and hedging a given contingent claim has a unique solution in a complete market framework. When some incompleteness is introduced, the problem becomes however more difficult. Several approaches have been adopted in the literature to provide a satisfactory answer to this problem, for a particular choice criterion. In this paper, in order to price and hedge a non-tradable contingent claim, we first start with a (standard) utility maximization problem and end up with an equivalent risk measure minimization. This hedging problem can be seen as a particular case of a more general situation of risk transfer between different agents, one of them consisting of the financial market. In order to provide constructive answers to this general optimal risk transfer problem, both static and dynamic approaches are considered. When considering a dynamic framework, our main purpose is to find a trade-off between static and very abstract risk measures as we are more interested in tractability issues and interpretations of the dynamic risk measures we obtain rather than the ultimate general results. Therefore, after introducing a general axiomatic approach to dynamic risk measures, we relate the dynamic version of convex risk measures to BSDEs.

http://arxiv.org/abs/0708.0948

5918. Law of Large Numbers Limits for Many Server Queues

Author(s): Haya Kaspi and Kavita Ramanan

Abstract: This work considers a many-server queueing system in which customers with i.i.d., generally distributed service times enter service in the order of arrival. The dynamics of the system is represented in terms of a process that describes the total number of customers in the system, as well as a measure-valued process that keeps track of the ages of customers in service. Under mild assumptions on the service time distribution, as the number of servers goes to infinity, a law of large numbers (or fluid) limit is established for this pair of processes. The limit is characterised as the unique solution to a coupled pair of integral equations, which admits a fairly explicit representation. As a corollary, the fluid limits of several other functionals of interest, such as the waiting time, are also obtained. Furthermore, in the time-homogeneous setting, the fluid limit is shown to converge to its equilibrium. Along the way, some results of independent interest are obtained, including a continuous mapping result and a maximality property of the fluid limit. A motivation for studying these systems is that they arise as models of computer data systems and call centers.

http://arxiv.org/abs/0708.0952

5919. Fine-tune your smile: Correction to Hagan et al

Author(s): Jan Obloj

Abstract: In this small note we use results derived in Berestycki et al. to correct the celebrated formulae of Hagan et al. We derive explicitly the correct zero order term in the expansion of the implied volatility in time to maturity. The new term is consistent as $\beta\to 1$. Furthermore, numerical simulations show that it reduces or eliminates known pathologies of the earlier formula.

http://arxiv.org/abs/0708.0998

5920. On deciding stability of multiclass queueing networks under buffer priority scheduling policies

Author(s): David Gamarnik and Dmitriy Katz

Abstract: One of the basic properties of a queueing network is stability. Roughly speaking it is the property that the total number of jobs in the network remains bounded as a function of time. One of the key questions related to the stability issue is determining the exact conditions under which a given queueing network operating under a given scheduling policy stable. While initially there was a lot of progress in addressing this question, most of the obtained results were partial at best, and the complete characterization of stable queueing networks is lacking. In this paper we resolve this important open problem, albeit in a somewhat unexpected way. We show that characterizing stable queueing networks is an algorithmically undecidable problem for the case of non-preemptive static buffer priority scheduling policies and deterministic interarrival and service times. Thus no constructive characterization of stable queueing networks operating under this class of policies is possible. Our approach builds on an earlier related work and uses the so-called counter machine device as a reduction tool.

http://arxiv.org/abs/0708.1034

5921. Densities for Ornstein-Uhlenbeck processes with jumps

Author(s): Enrico Priola and Jerzy Zabczyk

Abstract: We consider an Ornstein-Uhlenbeck process with values in R^n driven by a L\'evy process (Z_t) taking values in R^d with d possibly smaller than n. The L\'evy noise can have a degenerate or even vanishing Gaussian component. Under a controllability condition and an assumption on the L\'evy measure of (Z_t), we prove that the law of the Ornstein-Uhlenbeck process at any time t>0 has a density on R^n. Moreover, when the L\'evy process is of $\alpha $-stable type, $\alpha \in (0,2)$, we show that such density is a $C^{\infty}$- function.

http://arxiv.org/abs/0708.1084

5922. Stochastic Knapsack Problem Revisited: Switch-Over Policies and Dynamic Pricing

Author(s): Grace Lin and Yingdong Lu and David Yao

Abstract: The stochastic knapsack has been used as a model in wide ranging applications from dynamic resource allocation to admission control in telecommunication. In recent years, a variation of the model has become a basic tool in studying problems that arise in revenue management and dynamic/flexible pricing; and it is in this context that our study is undertaken. Based on a dynamic programming formulation and associated properties of the value function, we study in this paper a class of control that we call switch-over policies -- start from accepting only orders of the highest price, and switch to including lower prices as time goes by, with the switch-over times optimally decided via convex programming. We establish the asymptotic optimality of the switch- over policy, and develop pricing models based on this policy to optimize the price reductions over the decision horizon.

http://arxiv.org/abs/0708.1146

5923. Errors Theory using Dirichlet Forms, Linear Partial Differential Equations and Wavelets

Author(s): Simone Scotti

Abstract: We present an application of error theory using Dirichlet Forms in linear partial differential equations (LPDE). We study the transmission of an uncertainty on the terminal condition to the solution of the LPDE thanks to the decomposition of the solution on a wavelets basis. We analyze the basic properties and a particular class of LPDE where the wavelets bases show their powerful, the combination of error theory and wavelets basis justifies some hypotheses, helpful to simplify the computation.

http://arxiv.org/abs/0708.1073

5924. The marginalization paradox and the formal Bayes' law

Author(s): Timothy C. Wallstrom

Abstract: It has recently been shown that the marginalization paradox (MP) can be resolved by interpreting improper inferences as probability limits. The key to the resolution is that probability limits need not satisfy the formal Bayes' law, which is used in the MP to deduce an inconsistency. In this paper, I explore the differences between probability limits and the more familiar pointwise limits, which do imply the formal Bayes' law, and show how these differences underlie some key differences in the interpretation of the MP.

http://arxiv.org/abs/0708.1350

5925. Selfdecomposability and selfsimilarity: a concise primer

Author(s): Nicola Cufaro Petroni

Abstract: We summarize the relations among three classes of laws: infinitely divisible, selfdecomposable and stable. First we look at them as the solutions of the Central Limit Problem; then their role is scrutinized in relation to the Levy and the additive processes with an emphasis on stationarity and selfsimilarity. Finally we analyze the Ornstein-Uhlenbeck processes driven by Levy noises and their selfdecomposable stationary distributions, and we end with a few particular examples.

http://arxiv.org/abs/0708.1239

5926. Harnack inequality and applications for stochastic generalized porous media equations

Author(s): Feng-Yu Wang

Abstract: By using coupling and Girsanov transformations, the dimension-free Harnack inequality and the strong Feller property are proved for transition semigroups of solutions to a class of stochastic generalized porous media equations. As applications, explicit upper bounds of the $L^p$-norm of the density as well as hypercontractivity, ultracontractivity and compactness of the corresponding semigroup are derived.

http://arxiv.org/abs/0708.1671

5927. Curve crossing for random walks reflected at their maximum

Author(s): Ron Doney and Ross Maller

Abstract: Let $R_n=\max_{0\leq j\leq n}S_j-S_n$ be a random walk $S_n$ reflected in its maximum. Except in the trivial case when $P(X\ge0)=1$, $R_n$ will pass over a horizontal boundary of any height in a finite time, with probability 1. We extend this by giving necessary and sufficient conditions for finiteness of passage times of $R_n$ above certain curved (power law) boundaries, as well. The intuition that a degree of heaviness of the negative tail of the distribution of the increments of $S_n$ is necessary for passage of $R_n$ above a high level is correct in most, but not all, cases, as we show. Conditions are also given for the finiteness of the expected passage time of $R_n$ above linear and square root boundaries.

http://arxiv.org/abs/0708.1676

5928. Weak Solutions of Stochastic Differential Equations over the Field of p-Adic Numbers

Author(s): Hiroshi Kaneko and Anatoly N. Kochubei

Abstract: Study of stochastic differential equations on the field of p-adic numbers was initiated by the second author and has been developed by the first author, who proved several results for the p-adic case, similar to the theory of ordinary stochastic integral with respect to Levy processes on the Euclidean spaces. In this article, we present an improved definition of a stochastic integral on the field and prove the joint (time and space) continuity of the local time for p-adic stable processes. Then we use the method of random time change to obtain sufficient conditions for the existence of a weak solution of a stochastic differential equation on the field, driven by the p-adic stable process, with a Borel measurable coefficient.

http://arxiv.org/abs/0708.1706

5929. On the structure of general mean-variance hedging strategies

Author(s): Ale\v{s} \v{C}ern\'y and Jan Kallsen

Abstract: We provide a new characterization of mean-variance hedging strategies in a general semimartingale market. The key point is the introduction of a new probability measure $P^{\star}$ which turns the dynamic asset allocation problem into a myopic one. The minimal martingale measure relative to $P^{\star}$ coincides with the variance-optimal martingale measure relative to the original probability measure $P$.

http://arxiv.org/abs/0708.1715

5930. Dynamics of Jackson networks: perturbation theory

Author(s): Reuven Zeitak

Abstract: We introduce a new formalism for dealing with networks of queues. The formalism is based on the Doi-Peliti second quantization method for reaction diffusion systems. As a demonstration of the method's utility we compute perturbatively the different time busy-busy correlations between two servers in a Jackson network.

http://arxiv.org/abs/0708.1718

5931. On asymptotics of eigenvectors of large sample covariance matrix

Author(s): Z. D. Bai and B. Q. Miao and G. M. Pan

Abstract: Let \{$X_{ij}$\}, $i,j=...,$ be a double array of i.i.d. complex random variables with $EX_{11}=0,E|X_{11}|^2=1$ and $E|X_{11}|^4<\infty$, and let $A_n=\frac{1}{N}T_n^{{1}/{2}}X_nX_n^*T_n^{{1}/{2}}$, where $T_n^{{1}/ {2}}$ is the square root of a nonnegative definite matrix $T_n$ and $X_n$ is the $n\times N$ matrix of the upper-left corner of the double array. The matrix $A_n$ can be considered as a sample covariance matrix of an i.i.d. sample from a population with mean zero and covariance matrix $T_n$, or as a multivariate $F$ matrix if $T_n$ is the inverse of another sample covariance matrix. To investigate the limiting behavior of the eigenvectors of $A_n$, a new form of empirical spectral distribution is defined with weights defined by eigenvectors and it is then shown that this has the same limiting spectral distribution as the empirical spectral distribution defined by equal weights. Moreover, if \{$X_{ij}$\} and $T_n$ are either real or complex and some additional moment assumptions are made then linear spectral statistics defined by the eigenvectors of $A_n$ are proved to have Gaussian limits, which suggests that the eigenvector matrix of $A_n$ is nearly Haar distributed when $T_n$ is a multiple of the identity matrix, an easy consequence for a Wishart matrix.

http://arxiv.org/abs/0708.1720

5932. The infinite valley for a recurrent random walk in random environment

Author(s): Nina Gantert and Yuval Peres and Zhan Shi

Abstract: We consider a one-dimensional recurrent random walk in random environment (RWRE). We show that the - suitably centered - empirical distributions of the RWRE converge weakly to a certain limit law which describes the stationary distribution of a random walk in an infinite valley. The construction of the infinite valley goes back to Golosov. As a consequence, we show weak convergence for both the maximal local time and the self-intersection local time of the RWRE and also determine the exact constant in the almost sure upper limit of the maximal local time.

http://arxiv.org/abs/0708.1739

5933. Optimal execution strategies in limit order books with general shape functions

Author(s): Aur\'elien Alfonsi (CERMICS) and Alexander Schied and Antje Schulz

Abstract: Following Obizhaeva and Wang (2005), we consider optimal execution strategies for block market orders placed in a limit order book (LOB). Our main contribution is to allow for a general shape of the LOB defined via a given density function and thus to include the case of nonlinear price impact of market orders. In this setting, there are now two possibilities of modeling the resilience of the LOB after a large market order: the exponential recovery of the number of limit orders, i.e., of the volume of the LOB, or the exponential recovery of the bid-ask spread. We consider both situations and, in each case, derive explicit optimal execution strategies in discrete time. Applying our results to a block-shaped LOB, we obtain a new closed-form representation for the optimal strategy, which explicitly solves the recursive scheme given in Obizhaeva and Wang (2005). We also provide some evidence for the robustness of optimal strategies with respect to the choice of the shape function and the resilience-type.

http://arxiv.org/abs/0708.1756

5934. Spectra of random linear combinations of matrices defined via representations and Coxeter generators of the symmetric group

Author(s): Steven N. Evans

Abstract: We consider the asymptotic behavior as $n \to \infty$ of the spectra of random matrices of the form \[\frac{1}{\sqrt{n-1}} \sum_{k=1}^{n-1} Z_ {nk} \rho_n((k,k+1)),\] where for each $n$ the random variables $Z_{nk}$ are i.i.d. standard Gaussian and the matrices $\rho_n((k,k+1))$ are obtained by applying an irreducible unitary representation $\rho_n$ of the symmetric group on $\{1,2,...,n\}$ to the transposition $(k,k+1)$ that interchanges $k$ and $k+1$ (thus $\rho_n((k,k+1))$ is both unitary and self-adjoint, with all eigenvalues either +1 or -1). Irreducible representations of the symmetric group on $\{1,2,...,n\}$ are indexed by partitions $\lambda_n$ of $n$. A consequence of the results we establish is that if $\lambda_{n,1} \ge \lambda_{n,2} \ge ... \ge 0$ is the partition of $n$ corresponding to $\rho_n$, $\mu_{n,1} \ge \mu_{n,2} \ge ... \ge 0$ is the corresponding conjugate partition of $n$ (that is, the Young diagram of $\mu_n$ is the transpose of the Young diagram of $\lambda_n$), $\lim_{n \to \infty} \frac{\lambda_{n,i}}{n} = p_i$ for each $i \ge 1$, and $\lim_{n \to \infty} \frac{\mu_{n,j}}{n} = q_j$ for each $j \ge 1$, then the spectral measure of the resulting random matrix converges in distribution to a random probability measure that is Gaussian with mean $\theta Z$ and variance $1 - \theta^2$, where $\theta$ is the constant $ \sum_i p_i^2 - \sum_j q_j^2$ and $Z$ is a standard Gaussian random variable.

http://arxiv.org/abs/0708.1776

5935. Schramm-Loewner Equations Driven by Symmetric Stable Processes

Author(s): Zhen-Qing Chen and Steffen Rohde

Abstract: We consider shape, size and regularity of the hulls of the chordal Schramm-Loewner evolution driven by a symmetric alpha-stable process. We obtain derivative estimates, show that the complements of the hulls are Hoelder domains, prove that the hulls have Hausdorff dimension 1, and show that the trace is right-continuous with left limits almost surely.

http://arxiv.org/abs/0708.1805

5936. A random walk approximation to fractional Brownian motion

Author(s): Tom Lindstr{\o}m

Abstract: We present a random walk approximation to fractional Brownian motion where the increments of the fractional random walk are defined as a weighted sum of the past increments of a Bernoulli random walk.

http://arxiv.org/abs/0708.1905

5937. Stochastic bounds for two-layer loss systems

Author(s): Matthieu Jonckheere (Centrum voor Wiskunde en Informatica) and Lasse Leskel\"a (Eindhoven University of Technology)

Abstract: This paper studies multiclass loss systems with two layers of servers, where each server at the first layer is dedicated to a certain customer class, while the servers at the second layer can handle all customer classes. The routing of customers follows an overflow scheme, where arriving customers are preferentially directed to the first layer. Stochastic comparison and coupling techniques are developed for studying how the system is affected by packing of customers, altered service rates, and altered server configurations. This analysis leads to easily computable upper and lower bounds for the performance of the system.

http://arxiv.org/abs/0708.1927

5938. Two-parameter family of diffusion processes in the Kingman simplex

Author(s): Leonid Petrov

Abstract: The aim of the paper is to introduce a two-parameter family of infinite-dimensional diffusion processes X(alpha,theta) related to Pitman's two-parameter Poisson-Dirichlet distributions PD(alpha,theta). The diffusions X(alpha,theta) are obtained in a scaling limit transition from certain finite Markov chains on partitions of natural numbers. The state space of X(alpha,theta) is an infinite-dimensional simplex called the Kingman simplex. In the special case when parameter alpha vanishes, our finite Markov chains are similar to Moran-type model in population genetics, and our diffusion processes reduce to the infinitely-many-neutral-alleles diffusion model studied by Ethier and Kurtz (1981). Our main results extend those of Ethier and Kurtz to the two-parameter case and are as follows: The Poisson-Dirichlet distribution PD(alpha,theta) is a unique stationary distribution for the corresponding process X(alpha,theta); the process is ergodic and reversible; the spectrum of its generator is explicitly described. The general two-parameter case seems to fall outside the setting of models of population genetics, and our approach differs in some aspects from that of Ethier and Kurtz.

http://arxiv.org/abs/0708.1930

5939. Sparse graphs: metrics and random models

Author(s): B. Bollobas and O. Riordan

Abstract: Recently, Bollob\'as, Janson and Riordan introduced a very general family of random graph models, producing inhomogeneous random graphs with $ \Theta(n)$ edges. Roughly speaking, there is one model for each {\em kernel}, i.e., each symmetric measurable function from $[0,1]^2$ to the non-negative reals, although the details are much more complicated, to ensure the exact inclusion of many of the recent models for large-scale real-world networks. A different connection between kernels and random graphs arises in the recent work of Borgs, Chayes, Lov\'asz, S\'os, Szegedy and Vesztergombi. They introduced several natural metrics on dense graphs (graphs with $n$ vertices and $\Theta(n^2)$ edges), showed that these metrics are equivalent, and gave a description of the completion of the space of all graphs with respect to any of these metrics in terms of {\em graphons}, which are essentially kernels. One of the most appealing aspects of this work is the message that sequences of inhomogeneous quasi-random graphs are in a sense completely general: any sequence of dense graphs contains such a subsequence. Alternatively, their results show that certain natural models of dense inhomogeneous random graphs (one for each kernel) cover the space of dense graphs: there is one model for each point of the completion, producing graphs that converge to this point. Our aim here is to investigate to what extent the results above for dense graphs can be generalized to graphs with $o(n^2)$ edges. Although many of the definitions extend in a simple way, the connections between the various metrics, and between the metrics and random graph models, turn out to be much more complicated than in the dense case. We shall prove many partial results, and state even more conjectures and open problems.

http://arxiv.org/abs/0708.1919

5940. Tail Asymptotics and Estimation for Elliptical Distributions

Author(s): Enkelejd Hashorva

Abstract: Let (X,Y) be a bivariate elliptical random vector with associated random radius in the Gumbel max-domain of attraction. In this paper we obtain a second order asymptotic expansion of the joint survival probability P(X > x, Y> y) for x,y large. Further, based on the asymptotic bounds we discuss some aspects of the statistical modelling of joint survival probabilities and the survival conditional excess probability.

http://arxiv.org/abs/0708.1965

5941. Models with time-dependent parameters using transform methods: application to Heston's model

Author(s): A. Elices

Abstract: This paper presents a methodology to introduce time-dependent parameters for a wide family of models preserving their analytic tractability. This family includes hybrid models with stochastic volatility, stochastic interest-rates, jumps and their non-hybrid counterparts. The methodology is applied to Heston's model. A bootstrapping algorithm is presented for calibration. A case study works out the calibration of the time-dependent parameters to the volatility surface of the Eurostoxx 50 index. The methodology is also applied to the analytic valuation of forward start vanilla options driven by Heston's model. This result is used to explore the forward skew of the case study.

http://arxiv.org/abs/0708.2020

5942. Density-Profile Processes Describing Biological Signaling

Author(s): Roberto Fern\'andez and Luiz Renato Fontes and E. Jord\~ao Neves

Abstract: We introduce jump processes in R^k, called density-profile process, to model biological signaling networks. They describe the macroscopic evolution of finite-size spin-flip models with k types of spins interacting through a non-reversible Glauber dynamics. We focus on the the k-dimensional empirical-magnetization vector in the thermodynamic limit, and prove that, within arbitrary finite time-intervals, its path converges almost surely to a deterministic trajectory determined by a first-order (non-linear) differential equation. As parameters of the spin-flip dynamics change, the associated dynamical system may go through bifurcations, associated to phase transitions in the statistical mechanical setting. We present a simple example of spin-flip stochastic model leading to a dynamical system with Hopf and pitchfork bifurcations; depending on the parameter values, the magnetization random path can either converge to a unique stable fixed point, converge to one of a pair of stable fixed points, or asymptotically evolve close to a deterministic orbit in R^k.

http://arxiv.org/abs/0708.2044

5943. Nonantagonistic noisy duels of discrete type with an arbitrary number of actions

Author(s): Lyubov N. Positselskaya

Abstract: We study a nonzero-sum game of two players which is a generalization of the antagonistic noisy duel of discrete type. The game is considered from the point of view of various criterions of optimality. We prove existence of epsilon-equilibrium situations and show that the epsilon-equilibrium strategies that we have found are epsilon-maxmin. Conditions under which the equilibrium plays are Pareto-optimal are given. Keywords: noisy duel, payoff function, strategy, equilibrium situation, Pareto optimality, the value of a game.

http://arxiv.org/abs/0708.2023

5944. Rate of convergence to equilibrium for interacting particle systems via coupling and concentration

Author(s): Jean Ren\'e Chazottes and Pierre Collet and Frank Redig

Abstract: We present a new approach to estimate the relaxation speed to equilibrium of interacting particle systems. It is based on concentration inequalities and coupling. We illustrate our approach in a variety of examples for which we obtain several new results with short and non technical proofs. These examples include the symmetric and asymmetric exclusion process and high- temperature spin-flip dynamics ("Glauber dynamics"). We also give a direct proof of the Poincar\'e inequality, based on coupling, in the context of one- dimensional Gibbs measures with possibly long-range potentials.

http://arxiv.org/abs/0708.2152

5945. Alignment of one dimensional Gibbs measures

Author(s): Pierre Collet and Cristian Giardin\'a and Frank Redig

Abstract: We consider matching with shifts for Gibbsian sequences. We prove that the maximal overlap behaves as $c\log n$, where $c$ is explicitely identified in terms of the thermodynamic quantities (pressure) of the underlying potential. Our approach is based on the analysis of the first and second moment of the number of overlaps of a given size. We treat both the case of equal sequences (and non-zero shifts) and independent sequences.

http://arxiv.org/abs/0708.2165

5946. Stochastic Variational Integrators

Author(s): Nawaf Bou-Rabee and Houman Owhadi

Abstract: In this paper we introduce variational integrators for a class of stochastic mechanical systems driven by Wiener processes. The main result is to derive stochastic governing equations from a critical point of a stochastic action. With this result we derive Langevin-type equations for constrained mechanical systems, implement a stochastic analog of Lagrangian reduction, and design stochastic variational integrators.

http://arxiv.org/abs/0708.2187

5947. Connection between ordinary multinomials, generalized Fibonacci numbers, partial Bell partition polynomials and convolution powers of discrete uniform distribution

Author(s): Hacene Belbachir (USTHB) and Sadek Bouroubi (USTHB) and Abdelkader Khelladi (USTHB)

Abstract: Using an explicit computable expression of ordinary multinomials, we establish three remarkable connections, with the q-generalized Fibonacci sequence, the exponential partial Bell partition polynomials and the density of convolution powers of the discrete uniform distribution. Identities and various combinatorial relations are derived.

http://arxiv.org/abs/0708.2195

5948. Unimodality of ordinary multinomials and maximal probabilities of convolution powers of discrete uniform distribution

Author(s): Hacene Belbachir (USTHB)

Abstract: We establish the unimodality and the asymptotic strong unimodality of the ordinary multinomials and give their smallest mode leading to the expression of the maximal probability of convolution powers of the discrete uniform distribution. We conclude giving the generating functions of the sequence of generalized ordinary multinomials and for an extension of the sequence of maximal probabilities for convolution power of discrete uniform distribution.

http://arxiv.org/abs/0708.2341

5949. Non-intersecting paths and Hahn orthogonal polynomial ensemble

Author(s): Vadim Gorin

Abstract: We compute the bulk limit of the correlation functions for the uniform measure on lozenge tilings of a hexagon. The limiting determinantal process is a translation invariant extension of the discrete sine process, which also describes the ergodic Gibbs measure of an appropriate slope.

http://arxiv.org/abs/0708.2349

5950. Some explicit identities associated with positive self-similar Markov processes

Author(s): Loic Chaumont (LAREMA) and Andreas Kyprianou (UB) and Juan Carlos Pardo Millan (PMA, UB)

Abstract: We consider some special classes of L\'evy processes with no gaussian component whose L\'evy measure is of the type $\pi(dx)=e^{\gamma x}\nu (e^x-1) dx$, where $\nu$ is the density of the stable L\'evy measure and $ \gamma$ is a positive parameter which depends on its characteristics. These processes were introduced in \cite{CC} as the underlying L\'evy processes in the Lamperti representation of conditioned stable L\'evy processes. In this paper, we compute explicitly the law of these L\'evy processes at their first exit time from a finite or semi-finite interval, the law of their exponential functional and the first hitting time probability of a pair of points.

http://arxiv.org/abs/0708.2383

5951. On Semimeasures Predicting Martin-Loef Random Sequences

Author(s): Marcus Hutter and Andrej Muchnik

Abstract: Solomonoff's central result on induction is that the posterior of a universal semimeasure M converges rapidly and with probability 1 to the true sequence generating posterior mu, if the latter is computable. Hence, M is eligible as a universal sequence predictor in case of unknown mu. Despite some nearby results and proofs in the literature, the stronger result of convergence for all (Martin-Loef) random sequences remained open. Such a convergence result would be particularly interesting and natural, since randomness can be defined in terms of M itself. We show that there are universal semimeasures M which do not converge for all random sequences, i.e. we give a partial negative answer to the open problem. We also provide a positive answer for some non- universal semimeasures. We define the incomputable measure D as a mixture over all computable measures and the enumerable semimeasure W as a mixture over all enumerable nearly-measures. We show that W converges to D and D to mu on all random sequences. The Hellinger distance measuring closeness of two distributions plays a central role.

http://arxiv.org/abs/0708.2319

5952. The non-viscous Burgers equation associated with random positions in coordinate space: a threshold for blow up behaviour

Author(s): Sergio Albeverio and Olga Rozanova

Abstract: It is well known that the solutions to the non-viscous Burgers equation develop a gradient catastrophe at a critical time provided the initial data have a negative derivative in certain points. We consider this equation assuming that the particle paths in the medium are governed by a random process with a variance which depends in a polynomial way on the velocity. Given an initial distribution of the particles which is uniform in space and with the initial velocity linearly depending on the position we show both analytically and numerically that there exists a threshold effect: if the power in the above variance is less or equal 1, then the noise does not influence the solution behavior, in the following sense: the conditional expectation of the velocity given the position goes to infinity outside the origin. If however the power is larger than 1, then this conditional expectation decays to zero as the time tends to a critical value.

http://arxiv.org/abs/0708.2320

5953. A note on Talagrand's positivity principle

Author(s): Dmitry Panchenko

Abstract: Talagrand's positivity principle states that one can slightly perturb a Hamiltonian in the Sherrington-Kirkpatrick model in such a way that the overlap of two configurations under the perturbed Gibbs' measure will become typically nonnegative. In this note we observe that abstracting from the setting of the SK model only improves the result and does not require any modifications in Talagrand's argument. In this version, for example, positivity principle immediately applies to the setting of Aizenman-Sims-Starr interpolation. Also, abstracting from the SK model improves the conditions in the Ghirlanda-Guerra identities and as a consequence results in a perturbation of smaller order necessary to ensure positivity of the overlap.

http://arxiv.org/abs/0708.2453

5954. Existence, duality, and causality for Backward parabolic Ito equations

Author(s): Nikolai Dokuchaev

Abstract: We study existence, uniqueness, and a priori estimates for solutions for backward parabolic Ito equations in domains with boundary. The proofs are based duality between forward and backward equations. This duality is used also to establish that backward parabolic equations have some causality (more precisely, some anti-causality

http://arxiv.org/abs/0708.2497

5955. Hoeffding's inequality in game-theoretic probability

Author(s): Vladimir Vovk

Abstract: This note makes the obvious observation that Hoeffding's original proof of his inequality remains valid in the game-theoretic framework. All details are spelled out for the convenience of future reference.

http://arxiv.org/abs/0708.2502

5956. Pursuit-Evasion Games with Incomplete Information in Discrete Time

Author(s): Ori Gurel-Gurevich

Abstract: Pursuit-Evasion Games (in discrete time) are stochastic games with nonnegative daily payoffs, with the final payoff being the cumulative sum of payoffs during the game. We show that such games admit a value even in the presence of incomplete information and that this value is uniform, i.e. there are epsilon-optimal strategies for both players that are epsilon- optimal in any long enough prefix of the game. We give an example to demonstrate that nonnegativity is essential and expand the results to leavable games.

http://arxiv.org/abs/0708.2556

5957. Boundary Harnack Principle for Subordinate Brownian Motions

Author(s): Panki Kim and Renming Song and Zoran Vondracek

Abstract: We establish a boundary Harnack principle for a large class of subordinate Brownian motion, including mixtures of symmetric stable processes, in bounded $\kappa$-fat open set (disconnected analogue of John domains). As an application of the boundary Harnack principle, we identify the Martin boundary and the minimal Martin boundary of bounded $\kappa$-fat open sets with respect to these processes with their Euclidean boundary.

http://arxiv.org/abs/0708.2583

5958. Directed random growth models on the plane

Author(s): Timo Seppalainen

Abstract: This is a brief survey of laws of large numbers, fluctuation results and large deviation principles for asymmetric interacting particle systems that represent moving interfaces on the plane. We discuss the exclusion process, the Hammersley process and the related last-passage growth models.

http://arxiv.org/abs/0708.2721

5959. Stabilization of an overloaded queueing network using measurement-based admission control

Author(s): Lasse Leskel\"a

Abstract: Admission control can be employed to avoid congestion in queueing networks subject to overload. In distributed networks the admission decisions are often based on imperfect measurements on the network state. This paper studies how the lack of complete state information affects the system performance by considering a simple network model for distributed admission control. The stability region of the network is characterized and it is shown how feedback signaling makes the system very sensitive to its parameters.

http://arxiv.org/abs/0708.2739

5960. Maxima of Moving Sums in a Poisson Random Field

Author(s): Hock Peng Chan

Abstract: The extremal tail probabilities of moving sums in a marked Poisson random field is examined here. These sums are computed by adding up the weighted occurrences of events lying within a scanning set of fixed shape and size. Change of measure and analysis of local random fields are used to provide tail probabilities. The asymptotic constants are initially expressed in a form that seems hard to evaluate and do not seem to provide any additional information on the properties of the constants. A more sophisticated approach is then undertaken giving rise to an expression that is not only neater but also able to provide computable bounds. The technique used to obtain this constant can also be modified to work on continuous processes.

http://arxiv.org/abs/0708.2764

5961. A new metric between distributions of point processes

Author(s): Dominic Schuhmacher and Aihua Xia

Abstract: Most metrics between finite point measures currently used in the literature have the flaw that they do not treat differing total masses in an adequate manner for applications. This paper introduces a new metric $\bar{d}_1 $ that combines positional differences of points under a closest match with the relative difference in total mass in a way that fixes this flaw. A comprehensive collection of theoretical results about $\bar{d}_1$ and its induced Wasserstein metric $\bar{d}_2$ for point process distributions are given, including examples of useful $\bar{d}_1$-Lipschitz continuous functions, $\bar{d}_2$ upper bounds for Poisson process approximation, and $\bar {d}_2$ upper and lower bounds between distributions of point processes of i.i.d. points. Furthermore, we present a statistical test for multiple point pattern data that demonstrates the potential of $\bar{d}_1$ in applications.

http://arxiv.org/abs/0708.2777

5962. Random Matrices: The circular Law

Author(s): Terence Tao and Van Vu

Abstract: Let $\a$ be a complex random variable with mean zero and bounded variance $\sigma^{2}$. Let $N_{n}$ be a random matrix of order $n$ with entries being i.i.d. copies of $\a$. Let $\lambda_{1}, ..., \lambda_{n}$ be the eigenvalues of $\frac{1}{\sigma \sqrt n}N_{n}$. Define the empirical spectral distribution $\mu_{n}$ of $N_{n}$ by the formula $$ \mu_n(s,t) := \frac{1}{n} # \ {k \leq n| \Re(\lambda_k) \leq s; \Im(\lambda_k) \leq t \}.$$ The Circular law conjecture asserts that $\mu_{n}$ converges to the uniform distribution $\mu_\infty$ over the unit disk as $n$ tends to infinity. We prove this conjecture under the slightly stronger assumption that the $(2+\eta)\th$-moment of $\a$ is bounded, for any $\eta >0$. Our method builds and improves upon earlier work of Girko, Bai, G\"otze-Tikhomirov, and Pan-Zhou, and also applies for sparse random matrices. The new key ingredient in the paper is a general result about the least singular value of random matrices, which was obtained using tools and ideas from additive combinatorics.

http://arxiv.org/abs/0708.2895

5963. Diagrammatic bounds on the lace-expansion coefficients for oriented percolation

Author(s): Akira Sakai

Abstract: We provide a complete proof of the diagrammatic bounds on the lace- expansion coefficients for oriented percolation, which are used in [arXiv:math/ 0703455] to investigate critical behavior for long-range oriented percolation above 2\min{\alpha,2} spatial dimensions.

http://arxiv.org/abs/0708.2897

5964. Convergence of random zeros on complex manifolds

Author(s): Bernard Shiffman

Abstract: We show that the zeros of random sequences of Gaussian systems of polynomials of increasing degree almost surely converge to the expected limit distribution under very general hypotheses. In particular, the normalized distribution of zeros of systems of m polynomials of degree N, orthonormalized on a regular compact subset K of C^m, almost surely converge to the equilibrium measure on K as the degree N goes to infinity.

http://arxiv.org/abs/0708.2754

5965. Topology of randon linkages

Author(s): Michael Farber

Abstract: Betti numbers of configuration spaces of mechanical linkages (known also as polygon spaces) depend on a large number of parameters -- the lengths of the bars of the linkage. Motivated by applications in topological robotics, statistical shape theory and molecular biology, we view these lengths as random variables and study asymptotic values of the average Betti numbers as the number of links n tends to infinity. We establish a surprising fact that for a reasonably ample class of sequences of probability measures the asymptotic values of the average Betti numbers are independent of the choice of the measure. The main results of the paper apply to planar linkages as well as for linkages in R^3. We also prove results about higher moments of Betti numbers.

http://arxiv.org/abs/0708.2997

5966. Potential confinement property in the Parabolic Anderson Model

Author(s): Gabriela Gruninger and Wolfgang Konig

Abstract: We consider the parabolic Anderson model, the Cauchy problem for the heat equation with random potential in $Z^d$. We use i.i.d. potentials $ \xi: Z^d \to \R$ in the third universality class, namely the class of almost bounded potentials, in the classification of van der Hofstad, Konig and Morters [HKM06]. This class consists of potentials whose logarithmic moment generating function is regularly varying with parameter $\gamma=1$, but do not belong to the class of so-called double-exponentially distributed potentials studied by Gartner and Molchanov (PTRF 1998). In [HKM06] the asymptotics of the expected total mass was identified in terms of a variational problem that is closely connected to the well-known logarithmic Sobolev inequality and whose solution, unique up to spatial shifts, is a perfect parabola. In the present paper we show that those potentials whose shape (after appropriate vertical shifting and spatial rescaling) is away from that parabola contribute only negligibly to the total mass. The topology used is the strong $L^1$-topology on compacts for the exponentials of the potential. In the course of the proof, we show that any sequence of approximate minimisers of the above variational formula approaches some spatial shift of the minimiser, the parabola.

http://arxiv.org/abs/0708.3207

5967. Real Zeros and Normal Distribution for statistics on Stirling permutations defined by Gessel and Stanley

Author(s): Miklos Bona

Abstract: We study Stirling permutations defined by Gessel and Stanley in \cite{stangess}. We prove that their generating function according to the number of descents has real roots only. We use that fact to prove that the distribution of these descents, and other, equidistributed statistics on these objects converge to a normal distribution.

http://arxiv.org/abs/0708.3223

5968. Asymptotically Optimal Importance Sampling for Jackson Networks with a Tree Topology

Author(s): Ali Devin Sezer

Abstract: Importance sampling (IS) is a variance reduction method for simulating rare events. A recent paper by Dupuis, Wang and Sezer (Ann. App. Probab. 17 (4):1306- 1346, 2007) exploits connections between IS and stochastic games and optimal control problems to show how to design and analyze simple and efficient IS algorithms for various overflow events for tandem Jackson networks. The present paper uses the same approach to build asymptotically optimal IS schemes for stable open Jackson networks with a tree topology. Customers arrive at the single root of the tree. The rare overflow event we consider is the following: given that initially the network is empty, the system experiences a buffer overflow before returning to the empty state. Two types of buffer structures are considered: 1) A single system-wide buffer of size $n$ shared by all nodes, 2) each node $i$ has its own buffer of size $\beta_i n$, $\beta_i \in (0,1)$.

http://arxiv.org/abs/0708.3260

5969. Ergodic properties of a class of non-Markovian processes

Author(s): M. Hairer

Abstract: We study a fairly general class of time-homogeneous stochastic evolutions driven by noises that are not white in time. As a consequence, the resulting processes do not have the Markov property. In this setting, we obtain constructive criteria for the uniqueness of stationary solutions that are very close in spirit to the existing criteria for Markov processes. In the case of discrete time, where the driving noise consists of a stationary sequence of Gaussian random variables, we give optimal conditions on the spectral measure for our criteria to be applicable. In particular, we show that under a certain assumption on the spectral density, our assumptions can be checked in virtually the same way as one would check that the Markov process obtained by replacing the driving sequence by a sequence of independent identically distributed Gaussian random variables is strong Feller and topologically irreducible. The results of the present article are based on those obtained previously in the continuous time context of diffusions driven by fractional Brownian motion.

http://arxiv.org/abs/0708.3338

5970. Sharp phase transition and critical behaviour in 2D divide and colour models

Author(s): Andras Balint and Federico Camia and Ronald Meester

Abstract: Consider subcritical Bernoulli bond percolation with fixed parameter p

http://arxiv.org/abs/0708.3349

5971. Observability and nonlinear filtering

Author(s): Ramon van Handel

Abstract: This paper develops a connection between the asymptotic stability of nonlinear filters and a notion of observability. We consider a general class of hidden Markov models in continuous time with compact signal state space, and call such a model observable if no two initial measures of the signal process give rise to the same law of the observation process. We demonstrate that observability implies stability of the filter, i.e., the filtered estimates become insensitive to the initial measure at large times. For the special case where the signal is a finite-state Markov process and the observations are of the white noise type, a complete (necessary and sufficient) characterization of filter stability is obtained in terms of a slightly weaker detectability condition. In addition to observability, the role of controllability in filter stability is explored. Finally, the results are partially extended to non-compact signal state spaces.

http://arxiv.org/abs/0708.3412

5972. Fourth order BTP SPDEs on \Rp\times\Rd: Brownian-time random walk SDDEs limits solutions and dimension-dependent regularity for $1\le d\le3$

Author(s): Hassan Allouba

Abstract: Discretizing space and leaving time continuous, we view our recently introduced fourth order space-time white noise driven BTP SPDE through the eyes of their associated SDDEs (stochastic differential-difference equations) on $d$-dimensional spatial lattices. BTP SPDEs are stochastic equations in which the fourth order PDE part is solved by running our recently introduced Brownian-time processes (BTPs). To extend our SDDEs approach from second order SPDEs (see \cite{Adis,Asdde1,Asdde2}) to the fourth order BTP SPDEs, we introduce Brownian-time random walk (BTRW). We then formulate the associated SDDEs in terms of the density function of a BTRW on the spatial lattices. BTRWs are random walks whose clock $t$ is replaced with the Brownian clock $ \lab B_t\rab$, where $B$ is a Brownian motion. They are special cases of a new class of discrete-valued processes--which we introduce here as well--that we call Brownian-time chains (BTCs). BTCs are the discretized versions of BTPs. In this article, the density of BTRW plays the role of the Green function (Brownian motion density) for reaction diffusion (RD) and other second order equations. The system of BTRW SDDEs is a system of interacting diffusions representing the microscopic spatial behavior of the BTP SPDE. After defining the notion of BTRW SDDEs limits solutions to BTP SPDEs; we prove--among other things--the existence of such a solution to these equations in spatial dimensions $1\le d\le3$, under less-than-Lipschitz conditions on the diffusion coefficient. The paths of such a solution are H\"older continuous with a dimension- dependent exponent $\gamma\in\lpa 0,\tf{4-d}{8}\rpa$, $d=1,2,3$. This is in sharp contrast to RD SPDEs driven by space-time white noise, in which real- valued SDDEs weak limits solutions exist only in $d=1$.

http://arxiv.org/abs/0708.3419

5973. Asymptotic Behaviour of the Rate of Adaptation

Author(s): Charles Cuthbertson and Alison Etheridge and Feng Yu

Abstract: We consider the accumulation of beneficial and deleterious mutations in large asexual populations. The rate of adaptation is affected by the total mutation rate, proportion of beneficial mutations, and population size $N$. We show that regardless of mutation rates, as long as the proportion of beneficial mutations is strictly positive, the adaptation rate is at least $\Ocal(\log^{1- \delta} N)$, if the population size is sufficiently large. This shows that if the genome is modelled as continuous, there is no limit to natural selection.

http://arxiv.org/abs/0708.3453

5974. First Passage Densities and Boundary Crossing Probabilities for Diffusion Processes

Author(s): A. N. Downes and K. Borovkov

Abstract: We consider the boundary crossing problem for time-homogeneous diffusions and general curvilinear boundaries. Bounds are derived for the approximation error of the one-sided (upper) boundary crossing probability when replacing the original boundary by a different one. In doing so we establish the existence of the first-passage time density and provide an upper bound for this function. In the case of processes with diffusion interval equal to whole real line this is extended to a lower bound, as well as bounds for the first crossing time of a lower boundary. An extension to some time-inhomogeneous diffusions is given. These results are illustrated by numerical examples.

http://arxiv.org/abs/0708.3562

5975. Fractional Processes with Long-range Dependence

Author(s): Akihiko Inoue and Vo Van Anh

Abstract: We introduce a class of Gaussian processes with stationary increments which exhibit long-range dependence. The class includes fractional Brownian motion with Hurst parameter $H>1/2$ as a typical example. We establish infinite and finite past prediction formulas for the processes in which the predictor coefficients are given explicitly in terms of the MA$(\infty)$ and AR$ (\infty)$ coefficients. We apply the formulas to prove an analogue of Baxter's inequality, which concerns the $L^{1}$-estimate of the difference between the finite and infinite past predictor coefficients.

http://arxiv.org/abs/0708.3631

5976. Guerra's interpolation using Derrida-Ruelle cascades

Author(s): Dmitry Panchenko and Michel Talagrand

Abstract: New results about Poisson-Dirichlet point processes and Derrida- Ruelle cascades allow us to express Guerra's interpolation entirely in the language of Derrida-Ruelle cascades and to streamline Guerra's computations. Moreover, our approach clarifies the nature of the error terms along the interpolation.

http://arxiv.org/abs/0708.3641

5977. A note on the convergence of renewal and regenerative processes to a Brownian bridge

Author(s): Serguei Foss and Takis Konstantopoulos

Abstract: The standard functional central limit theorem for a renewal process with finite mean and variance, results in a Brownian motion limit. This note shows how to obtain a Brownian bridge process by a direct procedure that does not involve conditioning. Several examples are also considered.

http://arxiv.org/abs/0708.3667

5978. On topological spaces possessing uniformly distributed sequences

Author(s): V.I. Bogachev and M.N. Lukintsova

Abstract: Two classes of topological spaces are introduced on which every probability Radon measure possesses a uniformly distributed sequence or a uniformly tight uniformly distributed sequence. It is shown that these classes are stable under multiplication by completely regular Souslin spaces

http://arxiv.org/abs/0708.3486

5979. Densities for Rough Differential Equations under Hoermander's Condition

Author(s): Thomas Cass and Peter Friz

Abstract: We consider stochastic differential equations dY=V(Y)dX driven by a multidimensional Gaussian process X in the rough path sense. Using Malliavin Calculus we show that Y(t) admits a density for t in (0,T] provided (i) the vector fields V=(V_1,...,V_d) satisfy Hoermander's condition and (ii) the Gaussian driving signal X satisfies certain conditions. Examples of driving signals include fractional Brownian motion with Hurst parameter H>1/4, the Brownian Bridge returning to zero after time T and the Ornstein- Uhlenbeck process.

http://arxiv.org/abs/0708.3730

5980. Rate of Escape on Free Products

Author(s): Lorenz Gilch

Abstract: Suppose we are given the free product $V$ of a finite family of finite or countable sets $(V_i)_{i\in\mathcal{I}}$ and probability measures on each $V_i$, which govern random walks on it. We consider a transient random walk on the free product arising naturally from the random walks on the $V_i $. We prove the existence of the rate of escape with respect to the block length, that is, the speed, at which the random walk escapes to infinity, and furthermore we compute formulas for it. For this purpose, we present three different techniques providing three different, equivalent formulas.

http://arxiv.org/abs/0708.3763

5981. Rate of Escape on the Lamplighter Tree

Author(s): Lorenz Gilch

Abstract: Suppose we are given a homogeneous tree $\mathcal{T}_q$ of degree $q\geq 3$, where at each vertex sits a lamp, which can be switched on or off. This structure can be described by the wreath product $(\mathbb{Z}/2)\wr \Gamma$, where $\Gamma=\ast_{i=1}^q \mathbb{Z}/2$ is the free product group of $q$ factors $\mathbb{Z}/2$. We consider a transient random walk on a Cayley graph of $(\mathbb{Z}/2)\wr \Gamma$, for which we want to compute lower and upper bounds for the rate of escape, that is, the speed at which the random walk flees to infinity.

http://arxiv.org/abs/0708.3766

5982. Acceleration of Lamplighter Random Walks

Author(s): Lorenz Gilch

Abstract: Suppose we are given an infinite, finitely generated group $G$ and a transient random walk with bounded range on the wreath product $(\Z/ 2 \Z)\wr G$, such that its projection on $G$ is transient. This random walk can be interpreted as a lamplighter random walk, where there is a lamp at each element of $G$, which can be switched on and off, and a lamplighter walks along $G$ and switches lamps randomly on and off. Our aim is to show that the lamplighter random walk escapes with respect to a suitable (pseudo-)metric on the wreath product faster to infinity than its projection onto $G$. For this purpose, we show that the asymptotic linear rate of burning lamps is non-zero, providing an acceleration of the lamplighter. If lamp switches are not charged by the pseudo-metric and if $G\neq \Z$, we prove that the rate of escape with respect to the pseudo-metric, which becomes the length of a shortest ``travelling salesman tour'', is strictly bigger than the rate of escape of the lamplighter random walk's projection on $G$. We prove the same for non-degenerate cases if $G=\Z$. Furthermore, we prove for $G$ having infinitely many ends the acceleration with respect to a Markovian distance, which arises from probabilities on $(\Z/ 2\Z)\wr G$ and the metric on $G$.

http://arxiv.org/abs/0708.3767

5983. Applications of a finite-dimensional duality principle to some prediction problems

Author(s): Yukio Kasahara and Mohsen Pourahmadi and Akihiko Inoue

Abstract: Some of the most important results in prediction theory and time series analysis when finitely many values are removed from or added to its infinite past have been obtained using difficult and diverse techniques ranging from duality in Hilbert spaces of analytic functions (Nakazi, 1984) to linear regression in statistics (Box and Tiao, 1975). We unify these results via a finite-dimensional duality lemma and elementary ideas from the linear algebra. The approach reveals the inherent finite-dimensional character of many difficult prediction problems, the role of duality and biorthogonality for a finite set of random variables. The lemma is particularly useful when the number of missing values is small, like one or two, as in the case of Kolmogorov and Nakazi prediction problems. The stationarity of the underlying process is not a requirement. It opens up the possibility of extending such results to nonstationary processes.

http://arxiv.org/abs/0708.3895

5984. Is critical 2D percolation universal?

Author(s): Vincent Beffara (UMPA-Ensl)

Abstract: The aim of this paper is to explore possible ways of extending Smirnov's proof of Cardy's formula for critical site-percolation on the triangular lattice to other cases (such as bond-percolation on the square lattice); the main question we address is that of the choice of the lattice embedding into the plane which gives rise to conformal invariance in the scaling limit. Even though we were not able to produce a complete proof, we believe that the ideas presented here go in the right direction.

http://arxiv.org/abs/0708.3908

5985. Generalized Gamma Convolutions, Dirichlet means, Thorin measures, with explicit examples

Author(s): Lancelot F. James and Bernard Roynette and Marc Yor

Abstract: I. In Section 1, we present a number of classical results concerning the Generalized Gamma Convolution (: GGC) variables, their Wiener-Gamma representations, and relation with the Dirichlet processes. II. To a GGC variable, one may associate a unique Thorin measure. Let $G$ a positive r.v. and $\Gamma_{t} (G)$ \big(resp. $\Gamma_{t} (1/G)\big)$ the Generalized Gamma Convolution with Thorin measure $t$-times the law of $G$ (resp. the law of 1/G). In Section 2, we compare the laws of $\Gamma_ {t} (G)$ and $\Gamma_{t} (1/G)$. III. In Section 3, we present some old and some new examples of GGC variables, among which the lengths of excursions of Bessel processes straddling an independent exponential time.

http://arxiv.org/abs/0708.3932

5986. Epidemics on random graphs with tunable clustering

Author(s): Tom Britton and Maria Deijfen and Andreas Nordvall Lager{\aa}s and Mathias Lindholm

Abstract: In this paper, a branching process approximation for the spread of a Reed-Frost epidemic on a network with tunable clustering is derived. The approximation gives rise to expressions for the epidemic threshold and the probability of a large outbreak in the epidemic. It is investigated how these quantities varies with the clustering in the graph and it turns out for instance that, as the clustering increases, the epidemic threshold decreases. The network is modelled by a random intersection graph, in which individuals are independently members of a number of groups and two individuals are linked to each other if and only if they share at least one group.

http://arxiv.org/abs/0708.3939

5987. A critical constant for the k nearest neighbour model

Author(s): Paul Balister and Bela Bollobas and Amites Sarkar and Mark Walters

Abstract: Let P be a Poisson process of intensity one in a square S_n of area n. For a fixed integer k, join every point of P to its k nearest neighbours, creating an undirected random geometric graph G_{n,k}. We prove that there exists a critical constant c such that for c'c G_ {n,c'\log n} is connected with probability tending to 1 as n tends to infinity. This answers a question previously posed by the authors.

http://arxiv.org/abs/0708.4007

5988. Asymptotic Blocking Probabilities in Loss Networks with Subexponential Demands

Author(s): Yingdong Lu and Ana Radovanovi\'c

Abstract: The analysis of stochastic loss networks has long been of interest in computer and communications networks and is becoming important in the areas of service and information systems. In traditional settings, computing the well known Erlang formula for blocking probability in these systems becomes intractable for larger resource capacities. Using compound point processes to capture stochastic variability in the request process, we generalize existing models in this framework and derive simple asymptotic expressions for blocking probabilities. In addition, we extend our model to incorporate reserving resources in advance. Although asymptotic, our experiments show an excellent match between derived formulas and simulation results even for relatively small resource capacities and relatively large values of blocking probabilities.

http://arxiv.org/abs/0708.4059

5989. $L^2$-approximating pricing under restricted information

Author(s): M. Mania and R. Tevzadze and T. Toronjadze

Abstract: We consider the mean-variance hedging problem under partial information in the case where the flow of observable events does not contain the full information on the underlying asset price process. We introduce a martingale equation of a new type and characterize the optimal strategy in terms of the solution of this equation. We give relations between this equation and backward stochastic differential equations for the value process of the problem.

http://arxiv.org/abs/0708.4095

5990. A limit result for a system of particles in random environment

Author(s): Pierre Andreoletti (MAPMO)

Abstract: We consider an infinite system of particles in one dimension, each particle performs independant Sinai's random walk in random environment. Considering an instant $t$, large enough, we prove a result in probability showing that the particles are trapped in the neighborhood of well defined points of the lattice depending on the random environment the time $t$ and the starting point of the particles.

http://arxiv.org/abs/0708.4156

5991. On Martingale Approximations

Author(s): Ou Zhao and Michael Woodroofe

Abstract: Consider additive functionals of a Markov chain $W_k$, with stationary (marginal) distribution and transition function denoted by $\pi$ and $Q$, say $S_n = g(W_1)+...+g(W_n)$, where $g$ is square integrable and has mean 0 with respect to $\pi$. If $S_n$ has the form $S_n = M_n+R_n$, where $M_n$ is a square integrable martingale with stationary increments and $E(R_n^ {2}) = o(n)$, then $g$ is said to admit a martingale approximation. Necessary and sufficient conditions for such an approximation are developed. Let $Q^*$ denote the adjoint operator to $Q$, regarded as a linear operator from $L^2 (\pi)$ into itself, and consider co-isometries ($QQ^{*} = I$), an important special case that includes shift processes. In one main result a convenient orthonormal basis for $L_0^{2}(\pi)$ is identified along with a simple necessary and sufficient condition for the existence of a martingale approximation in terms of the coefficients of the expansion of $g$ with respect to this basis. Two obvious necessary conditions for a martingale approximation are $E[E(S_n|W_1)^2] = o(n)$ and $\lim_{n\to\infty} E(S_n^{2})/n < \infty$. Assuming the first of these, let $\Vert g\Vert^2_{+} = \limsup_{n\to \infty} E(S_n^{2})/n$. Then $\Vert\cdot\Vert_{+}$ defines a pseudo norm on the subspace of $L^2(\pi)$ where it is finite. In another main result, a simple necessary and sufficient condition for a martingale approximation is developed in terms of $\Vert\cdot\Vert_{+}$.

http://arxiv.org/abs/0708.4183

5992. On hitting times and fastest strong stationary times for skip- free chains

Author(s): James Allen Fill

Abstract: An (upward) skip-free Markov chain with the set of nonnegative integers as state space is a chain for which upward jumps may be only of unit size; there is no restriction on downward jumps. In a 1987 paper, Brown and Shao determined, for an irreducible continuous-time skip-free chain and any d, the passage time distribution from state 0 to state d. When the nonzero eigenvalues nu_j of the generator are all real, their result states that the passage time is distributed as the sum of d independent exponential random variables with rates nu_j. We give another proof of their theorem. In the case of birth-and-death chains, our proof leads to an explicit representation of the passage time as a sum of independent exponential random variables. Diaconis and Miclo recently obtained the first such representation, but our construction is much simpler. We obtain similar (and new) results for a fastest strong stationary time T of an ergodic continuous-time skip-free chain with stochastically monotone time-reversal started in state 0, and we also obtain discrete-time analogs of all our results.

http://arxiv.org/abs/0708.4258

5993. Dynamical sensitivity of the infinite cluster in critical percolation

Author(s): Yuval Peres and Oded Schramm and Jeffrey E. Steif

Abstract: In dynamical percolation, the status of every bond is refreshed according to an independent Poisson clock. For graphs which do not percolate at criticality, the dynamical sensitivity of this property was analyzed extensively in the last decade. Here we focus on graphs which percolate at criticality, and investigate the dynamical sensitivity of the infinite cluster. We first give two examples of bounded degree graphs, one which percolates for all times at criticality and one which has exceptional times of nonpercolation. We then make a nearly complete analysis of this question for spherically symmetric trees with spherically symmetric edge probabilities bounded away from 0 and 1. One interesting regime occurs when the expected number of vertices at the nth level that connect to the root at a fixed time is of order n(\log n)^ \alpha. R. Lyons (1990) showed that at a fixed time, there is an infinite cluster a.s. if and only if \alpha >1. We prove that the probability that there is an infinite cluster at all times is 1 if \alpha > 2, while this probability is 0 if 1<\alpha \le 2. Within the regime where a.s. there is an infinite cluster at all times, there is yet another type of ``phase transition'' in the behavior of the process: if the expected number of vertices at the nth level connecting to the root at a fixed time is of order n^\theta with \theta > 2, then the number of connected components of the set of times in [0,1] at which the root does not percolate is finite a.s., while if 1<\theta < 2, then the number of such components is infinite with positive probability.

http://arxiv.org/abs/0708.4287

5994. Large Sample Asymptotics for the Two Parameter Poisson Dirichlet Process

Author(s): Lancelot F. James

Abstract: This paper explores large sample properties of the two parameter $(\alpha,\theta)$ Poisson-Dirichlet Process in two contexts. In a Bayesian context of estimating an unknown probability measure, viewing this process as a natural extension of the Dirichlet process, we explore the consistency and weak convergence of the the two parameter Poisson Dirichlet posterior process. We also establish the weak convergence of properly centered two parameter Poisson Dirichlet processes for large $\theta+n\alpha.$ This latter result complements large $\theta$ results for the Dirichlet process and Poisson Dirichlet sequences, and complements a recent result on large deviation principles for the two parameter Poisson Dirichlet process. A crucial component of our results is the use of distributional identities that may be useful in other contexts.

http://arxiv.org/abs/0708.4294

5995. The size of a pond in 2D invasion percolation

Author(s): Jacob van den Berg and Antal A. J\'arai and B\'alint V\'agv\"olgyi

Abstract: We consider invasion percolation on the square lattice. It has been proved by van den Berg, Peres, Sidoravicius and Vares, that the probability that the radius of a so-called pond is larger than n, differs at most a factor of order log n from the probability that in critical Bernoulli percolation the radius of an open cluster is larger than n. We show that these two probabilities are, in fact, of the same order. Moreover, we prove an analogous result for the volume of a pond.

http://arxiv.org/abs/0708.4369

5996. The largest component in a subcritical random graph with a power law degree distribution

Author(s): Svante Janson

Abstract: It is shown that in a subcritical random graph with given vertex degrees satifying a power law degree distribution with exponent \gamma>3, the largest component is of order n^{1/(\gamma-1)}. More precisely, the order of the largest component is approximatively given by a simple constant times the largest vertex degree. These results are extended to several other random graph models with power law degree distributions. This proves a conjecture by Durrett.

http://arxiv.org/abs/0708.4404
stefano . iacus at unimi . it