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We present elliptical processes, a family of non-parametric probabilistic models that subsume Gaussian processes and Student's t processes. This generalization includes a range of new heavy-tailed behaviors while retaining computational…

Machine Learning · Computer Science 2023-11-23 Maria Bånkestad , Jens Sjölund , Jalil Taghia , Thomas B. Schöon

We analyze a class of continuous time random walks in $\mathbb R^d,d\geq 2,$ with uniformly distributed directions. The steps performed by these processes are distributed according to a generalized Dirichlet law. Given the number of changes…

Probability · Mathematics 2015-06-16 Alessandro De Gregorio

A deterministic walk in a random environment can be understood as a general random process with finite-range dependence that starts repeating a loop once it reaches a site it has visited before. Such process lacks the Markov property. We…

Probability · Mathematics 2012-10-15 Ivan Matic

We study a linear-fractional Bienaym\'e-Galton-Watson process with a general type space. The corresponding tree contour process is described by an alternating random walk with the downward jumps having a geometric distribution. This leads…

Probability · Mathematics 2016-03-07 Alexey Lindo , Serik Sagitov

A very simple event frequency approximation algorithm that is sensitive to event timeliness is suggested. The algorithm iteratively updates categorical click-distribution, producing (path of) a random walk on a standard $n$-dimensional…

Numerical Analysis · Mathematics 2019-05-29 Alexander Kushkuley

Representations based on random walks can exploit discrete data distributions for clustering and classification. We extend such representations from discrete to continuous distributions. Transition probabilities are now calculated using a…

Machine Learning · Computer Science 2012-12-12 Chen-Hsiang Yeang , Martin Szummer

The double Pareto distribution is a heavy-tailed distribution with a power-law tail, that is generated via geometric Brownian motion with an exponentially distributed observation time. In this study, we examine a modified model wherein the…

Statistical Mechanics · Physics 2024-04-30 Ken Yamamoto , Takashi Bando , Hirokazu Yanagawa , Yoshihiro Yamazaki

In extreme value statistics, the peaks-over-threshold method is widely used. The method is based on the generalized Pareto distribution characterizing probabilities of exceedances over high thresholds in $\mathbb {R}^d$. We present a…

Probability · Mathematics 2014-10-17 Ana Ferreira , Laurens de Haan

We consider random walks and L\'evy processes in a homogeneous group $G$. For all $p > 0$, we completely characterise (almost) all $G$-valued L\'evy processes whose sample paths have finite $p$-variation, and give sufficient conditions…

Probability · Mathematics 2018-06-18 Ilya Chevyrev

We consider a continuous-time random walk which is defined as an interpolation of a random walk on a point process on the real line. The distances between neighboring points of the point process are i.i.d. random variables in the normal…

Probability · Mathematics 2020-01-08 Alessandra Bianchi , Marco Lenci , Françoise Pène

Rare events in stochastic processes with heavy-tailed distributions are controlled by the big jump principle, which states that a rare large fluctuation is produced by a single event and not by an accumulation of coherent small deviations.…

Statistical Mechanics · Physics 2020-03-13 Raffaella Burioni , Alessandro Vezzani

Consider a stochastic process that behaves as a $d$-dimensional simple and symmetric random walk, except that, with a certain fixed probability, at each step, it chooses instead to jump to a given site with probability proportional to the…

Probability · Mathematics 2020-08-26 Cécile Mailler , Gerónimo Uribe Bravo

The emergence of heavy-tailed statistics in complex systems is conventionally attributed to non-local stochastic jumps or non-Markovian memory. Here, we present a one-dimensional random walk where power-law behaviors arise instead from a…

Statistical Mechanics · Physics 2026-05-25 Henrique S. Lima , Evaldo M. F. Curado

A new model that maps a quantum random walk described by a Hadamard operator to a particular case of a random walk is presented. The model is represented by a Markov chain with a stochastic matrix, i.e., all the transition rates are…

Quantum Physics · Physics 2020-11-18 Arie Bar-Haim

The involution walk is the random walk on $S_n$ generated by involutions with a binomially distributed with parameter $1-p$ number of $2$-cycles. This is a parallelization of the transposition walk. The involution walk is shown in this…

Combinatorics · Mathematics 2016-07-05 Megan Bernstein

Motivated by discrete kinetic models for non-cooperative molecular motors on periodic tracks, we consider random walks (also not Markov) on quasi one dimensional (1d) lattices, obtained by gluing several copies of a fundamental graph in a…

Statistical Mechanics · Physics 2017-04-26 Alessandra Faggionato , Vittoria Silvestri

We consider a continuous-time random walk which is the generalization, by means of the introduction of waiting periods on sites, of the one-dimensional nonhomogeneous random walk with a position-dependent drift known in the mathematical…

Statistical Mechanics · Physics 2021-10-25 Gaia Pozzoli , Mattia Radice , Manuele Onofri , Roberto Artuso

We survey recent results on some one- and two-dimensional patterns generated by random permutations of natural numbers. In the first part, we discuss properties of random walks, evolving on a one-dimensional regular lattice in discrete time…

Statistical Mechanics · Physics 2009-11-11 G. Oshanin , R. Voituriez , S. Nechaev , O. Vasilyev , F. Hivert

We study the evolution of a random walker on a conservative dynamic random environment composed of independent particles performing simple symmetric random walks, generalizing results of [16] to higher dimensions and more general transition…

We consider trawl processes, which are stationary and infinitely divisible stochastic processes and can describe a wide range of statistical properties, such as heavy tails and long memory. In this paper, we develop the first…

Methodology · Statistics 2023-08-31 Dan Leonte , Almut E. D. Veraart