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I show how any reversible Markov chain on a finite state space that is irreducible, and hence suitable for estimating expectations with respect to its invariant distribution, can be used to construct a non-reversible Markov chain on a…

Probability · Mathematics 2007-06-13 Radford M. Neal

There is a wide literature on change point tests, but the case of variables with infinite variances is essentially unexplored. In this paper we address this problem by studying the asymptotic behavior of trimmed CUSUM statistics. We show…

Statistics Theory · Mathematics 2012-01-06 István Berkes , Lajos Horváth , Johannes Schauer

With motivation from K. D\c{e}bicki and P. Kisowski (2007), in this paper we derive the exact tail asymptotics of $\alpha(t)$-locally stationary Gaussian processes with non-constant variance functions. We show that some certain variance…

Probability · Mathematics 2016-08-23 Long Bai

Linear fractional Galton-Watson branching processes in i.i.d.~random environment are, on the quenched level, intimately connected to random difference equations by the evolution of the random parameters of their linear fractional marginals.…

Probability · Mathematics 2021-10-01 Gerold Alsmeyer

In this work, we consider an inhomogeneous (discrete time) Markov chain and are interested in its long time behavior. We provide sufficient conditions to ensure that some of its asymptotic properties can be related to the ones of a…

Probability · Mathematics 2017-11-09 Michel Benaïm , Florian Bouguet , Bertrand Cloez

In this paper, we first investigate the monotonicity and limit problem of the fractional integral functions. By fixed point theorem and these new results of the fractional integral functions, we present that the Riemann-Liouville fractional…

Classical Analysis and ODEs · Mathematics 2023-08-30 Tao Zhu

We develop a martingale approximation approach to studying the limiting behavior of quadratic forms of Markov chains. We use the technique to examine the asymptotic behavior of lag-window estimators in time series and we apply the results…

Probability · Mathematics 2011-08-16 Yves F. Atchade , Matias D. Cattaneo

We introduce a general theory on stationary approximations for locally stationary continuous-time processes. Based on the stationary approximation, we use $\theta$-weak dependence to establish laws of large numbers and central limit type…

Probability · Mathematics 2022-03-01 Robert Stelzer , Bennet Ströh

A semi-martingale reflecting Brownian motion is a popular process for diffusion approximations of queueing models including their networks. In this paper, we are concerned with the case that it lives on the nonnegative half-line, but the…

Probability · Mathematics 2024-08-13 Masakiyo Miyazawa

The linear fractional stable motion generalizes two prominent classes of stochastic processes, namely stable L\'evy processes, and fractional Brownian motion. For this reason it may be regarded as a basic building block for continuous time…

Statistics Theory · Mathematics 2022-08-17 Fabian Mies , Mark Podolskij

Many systems across the sciences evolve through a combination of multiplicative growth and diffusive transport. In the presence of disorder, these systems tend to form localized structures which alternate between long periods of relative…

Statistical Mechanics · Physics 2022-12-19 Matteo Smerlak

In the recent article D\"oring et al. [4] the authors conditioned a stable process with two-sided jumps to avoid an interval. As usual the strategy was to find an invariant function for the process killed on entering the interval and to…

Probability · Mathematics 2020-02-19 Pierre Lenthe , Philip Weissmann

There is a well-established theory linking certain semi-Markov chains and continuous-time random walks to time-fractional equations and anomalous diffusion. In this work, we go beyond the semi-Markov framework by considering some…

Probability · Mathematics 2026-02-27 Lorenzo Facciaroni , Costantino Ricciuti , Enrico Scalas

We introduce a variational theory for processes adapted to the multi-dimensional Brownian motion filtration. The theory provides a differential structure which describes the infinitesimal evolution of Wiener functionals at very small…

Probability · Mathematics 2017-07-13 Alberto Ohashi , Dorival Leão , Alexandre B. Simas

Let $Z_t^{(0,\infty)}$ be the point process formed by the positions of all particles alive at time $t$ in a branching Brownian motion with drift and killed upon reaching 0. We study the asymptotic expansions of $Z_t^{(0,\infty)}(A)$ for $A=…

Probability · Mathematics 2023-07-21 Haojie Hou , Yan-Xia Ren , Renming Song

Eigenproblems frequently arise in theory and applications of stochastic processes, but only a few have explicit solutions. Those which do, are usually solved by reduction to the generalized Sturm--Liouville theory for differential…

Probability · Mathematics 2018-03-06 P. Chigansky , M. Kleptsyna , D. Marushkevych

We establish almost sure invariance principles, a strong form of approximation by Brownian motion, for non-stationary time-series arising as observations on dynamical systems. Our examples include observations on sequential expanding maps,…

Dynamical Systems · Mathematics 2014-06-18 N. Haydn , M. Nicol , A. Tôrôk , S. Vaienti

We consider the class of simple Brown-Resnick max-stable processes whose spectral processes are continuous exponential martingales. We develop the asymptotic theory for the realized power variations of these max-stable processes, that is,…

Statistics Theory · Mathematics 2019-06-11 Christian Y. Robert

We extend to Markov-modulated Brownian motion (MMBM) the renewal approach which has been successfully applied to the analysis of Markov-modulated fluid models. It has recently been shown that MMBM may be expressed as the limit of a…

Probability · Mathematics 2014-03-12 Guy Latouche , Giang T. Nguyen

We compute the exact asymptotics for the cumulants of linear statistics associated with the zeros counting measure of a large class of real Gaussian processes. Precisely, we show that if the underlying covariance function is regular and…

Probability · Mathematics 2023-10-09 Louis Gass
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