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In this note, we are concerned with the subgeometric rate of convergence of a Markov chain with discrete time parameter to its invariant measure in the $f$-norm. We clarify how three typical subgeometric rates of convergence are inherited…

Probability · Mathematics 2019-01-08 Chang-Song Deng

In this paper, we consider a type of time-changed Markov process, where the time-change is an inverse killed subordinator. This can be seen as an extension of Chen (Chen, Z., Time fractional equations and probabilistic representation, Chaos…

Probability · Mathematics 2019-12-09 Huiyan Zhao , Siyan xu

We establish subgeometric bounds on convergence rate of general Markov processes in the Wasserstein metric. In the discrete time setting we prove that the Lyapunov drift condition and the existence of a "good" $d$-small set imply…

Probability · Mathematics 2014-03-20 Oleg Butkovsky

A powerful tool for studying long-term convergence of a Markov process to its stationary distribution is a Lyapunov function. In some sense, this is a substitute for eigenfunctions. For a stochastically ordered Markov process on the…

Probability · Mathematics 2021-03-01 Andrey Sarantsev

Studying the subexponential convergence towards equilibrium of a strong Markov process, we exhibit an intermediate Lyapunov condition equivalent to the control of some moment of a hitting time. This provides a link, similar (although more…

Probability · Mathematics 2021-08-03 Armand Bernou

The paper discusses the continuous-time Markov Branching Process allowing Immigration. We are considering a critical case for which the second moment of offspring law and the first moment of immigration law are possibly infinite. Assuming…

Probability · Mathematics 2024-06-28 Azam Imomov

In this paper, we study the existence and uniqueness of solutions for general fractional-time parabolic equations of mixture type, and their probabilistic representations in terms of the corresponding inverse subordinators with or without…

Probability · Mathematics 2019-11-04 Zhen-Qing Chen

The convergence rate in Wasserstein distance is estimated for empirical measures of ergodic Markov processes, and the estimate can be sharp in some specific situations. The main result is applied to subordinations of typical models excluded…

Probability · Mathematics 2024-08-14 Feng-Yu Wang

Exponential relaxation to equilibrium is a typical property of physical systems, but inhomogeneities are known to distort the exponential relaxation curve, leading to a wide variety of relaxation patterns. Power law relaxation is related to…

Probability · Mathematics 2018-08-22 Mark M. Meerschaert , Bruno Toaldo

In this article densities (and their derivatives) of subordinators and inverse subordinators are considered. Under minor restrictions, generally milder than the existing in the literature, using a useful modification of the saddle point…

Probability · Mathematics 2024-02-12 Giacomo Ascione , Mladen Savov , Bruno Toaldo

Let $X:=(X_t)_{t\geq 0}$ be an ergodic Markov process on $\real^d$, and $p>0$. We derive upper bounds of the $p$-Wasserstein distance between the invariant measure and the empirical measures of the Markov process $X$. For this we assume,…

Probability · Mathematics 2025-12-30 René L. Schilling , Jian Wang , Bingyao Wu , Jie-Xiang Zhu

In this paper we consider the convergence of the conditional entropy to the entropy rate for Markov chains. Convergence of certain statistics of long range dependent processes, such as the sample mean, is slow. It has been shown in Carpio…

Probability · Mathematics 2021-10-29 Andrew Feutrill , Matthew Roughan

For discrete-time stochastic processes, there is a close connection between return/waiting times and entropy. Such a connection cannot be straightforwardly extended to the continuous-time setting. Contrarily to the discrete-time case one…

Probability · Mathematics 2007-05-23 Jean-Rene Chazottes , Cristian Giardina , Frank Redig

In this paper we investigate the long time behavior of solutions to fractional in time evolution equations which appear as results of random time changes in Markov processes. We consider inverse subordinators as random times and use the…

Probability · Mathematics 2020-06-25 Anatoly N. Kochubei , Yuri Kondratiev , José L. da Silva

We study a Markov process with two components: the first component evolves according to one of finitely many underlying Markovian dynamics, with a choice of dynamics that changes at the jump times of the second component. The second…

Probability · Mathematics 2015-04-14 Bertrand Cloez , Martin Hairer

In this paper, a method to exactly sample the trajectories of inverse subordinators (in the sense of the finite-dimensional distributions), jointly with the undershooting or overshooting process, is provided. The method applies to general…

Probability · Mathematics 2025-11-05 Ivan Biočić , Daniel E. Cedeño-Girón , Bruno Toaldo

In this paper we introduce non-decreasing jump processes with independent and time non-homogeneous increments. Although they are not L\'evy processes, they somehow generalize subordinators in the sense that their Laplace exponents are…

Probability · Mathematics 2016-03-10 Enzo Orsingher , Costantino Ricciuti , Bruno Toaldo

Consideration is given to the three different analytical methods for the computation of upper bounds for the rate of convergence to the limiting regime of one specific class of (in)homogeneous continuous-time Markov chains. This class is…

In this paper we study Green measures for certain classes of random time change Markov processes where the random time change are inverse subordinators. We show the existence of the Green measure for these processes under the condition of…

Probability · Mathematics 2020-08-11 José L. da Silva , Yuri Kondratiev

We study time-changed Markov processes to speed up the convergence of Markov chain Monte Carlo (MCMC) algorithms. The time-changed process is defined by adjusting the speed of time of a base process via a user-chosen, state-dependent…

Computation · Statistics 2025-04-08 Andrea Bertazzi , Giorgos Vasdekis
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