English
Related papers

Related papers: Ergodic properties for \alpha-CIR models and a cla…

200 papers

Consider a Markov chain $\{X_n\}_{n\ge 0}$ with an ergodic probability measure $\pi$. Let $\Psi$ a function on the state space of the chain, with $\alpha$-tails with respect to $\pi$, $\alpha\in (0,2)$. We find sufficient conditions on the…

Probability · Mathematics 2009-12-15 Milton Jara , Tomasz Komorowski , Stefano Olla

This paper provides a general and abstract approach to approximate ergodic regimes of Markov and Feller processes. More precisely, we show that the recursive algorithm presented in Lamberton & Pages (2002) and based on simulation algorithms…

Probability · Mathematics 2018-01-17 Gilles Pagès , Clément Rey

In this work, we study ergodicity of continuous time Markov processes on state space $\mathbb{R}_{\geq 0} := [0,\infty)$ obtained as unique strong solutions to stochastic equations with jumps. Our first main result establishes exponential…

Probability · Mathematics 2019-02-11 Martin Friesen , Peng Jin , Jonas Kremer , Barbara Rüdiger

This paper studies maximisation of an average-cost-per-unit-time ergodic functional over impulse strategies controlling a Feller-Markov process. The uncontrolled process is assumed to be ergodic but, unlike the extant literature, the…

Optimization and Control · Mathematics 2024-02-06 Jan Palczewski , Lukasz Stettner

We study the infinite-horizon average (ergodic) risk sensitive control problem for diffusion processes under a general structural hypothesis: there is a partition of state space into two subsets, where the controlled diffusion process…

Optimization and Control · Mathematics 2025-12-01 Sumith Reddy Anugu , Guodong Pang

This study explores a Gaussian quasi-likelihood approach for estimating parameters of diffusion processes with Markovian regime switching. Assuming the ergodicity under high-frequency sampling, we will show the asymptotic normality of the…

Statistics Theory · Mathematics 2025-05-19 Yuzhong Cheng , Hiroki Masuda

We study various classes of random processes defined on the regular tree $T_d$ that are invariant under the automorphism group of $T_d$. Most important ones are factor of i.i.d. processes (randomized local algorithms), branching Markov…

Probability · Mathematics 2015-07-28 Ágnes Backhausz , Balázs Szegedy

We provide quantitative bounds for the long time behavior of a class of Piecewise Deterministic Markov Processes with state space Rd \times E where E is a finite set. The continuous component evolves according to a smooth vector field that…

Probability · Mathematics 2012-12-07 Michel Benaïm , Stéphane Le Borgne , Florent Malrieu , Pierre-André Zitt

Examples of stochastic processes whose state space representations involve functions of an integral type structure $$I_{t}^{(a,b)}:=\int_{0}^{t}b(Y_{s})e^{-\int_{s}^{t}a(Y_{r})dr}ds, \quad t\ge 0$$ are studied under an ergodic…

Probability · Mathematics 2025-02-25 Abhishek Pal Majumder

Consider the continuous-time Markov Branching Process. In critical case we consider a situation when the generating function of intensity of transformation of particles has the infinite second moment, but its tail regularly varies in sense…

Probability · Mathematics 2022-01-07 Azam Imomov

We consider an irreducible pure jump Markov process with rates Q=(q(x,y)) on \Lambda\cup\{0\} with \Lambda countable and 0 an absorbing state. A quasi-stationary distribution (qsd) is a probability measure \nu on \Lambda that satisfies:…

Probability · Mathematics 2011-11-09 Pablo A. Ferrari , Nevena Maric

This paper provides a construction of a Fleming--Viot measure valued diffusion process, for which the transition function is known, by extending recent ideas of the Gibbs sampler based Markov processes. In particular, we concentrate on the…

Probability · Mathematics 2007-05-23 Stephen G. Walker , Spyridon J. Hatjispyros , Theodoros Nicoleris

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

A piecewise-deterministic Markov process is a stochastic process whose behavior is governed by an ordinary differential equation punctuated by random jumps occurring at random times. We focus on the nonparametric estimation problem of the…

Statistics Theory · Mathematics 2016-05-24 Romain Azaïs , Aurélie Muller-Gueudin

In this paper, we are interested in conditional McKean-Vlasov jump diffusions, which are also termed as McKean-Vlasov stochastic differential equations with jump idiosyncratic noise and jump common noise. As far as conditional McKean-Vlasov…

Probability · Mathematics 2025-09-03 Jianhai Bao , Yao Liu , Jian Wang

We study the relationship between two classical approaches for quantitative ergodic properties : the first one based on Lyapunov type controls and popularized by Meyn and Tweedie, the second one based on functional inequalities (of…

Probability · Mathematics 2007-05-23 Dominique Bakry , Patrick Cattiaux , Arnaud Guillin

In the framework of statistical mechanics the properties of macroscopic systems are deduced starting from the laws of their microscopic dynamics. One of the key assumptions in this procedure is the ergodic property, namely the equivalence…

Statistical Mechanics · Physics 2024-01-09 Marco Baldovin , Raffaele Marino , Angelo Vulpiani

We study the Fleming-Viot particle process formed by N interacting continuous-time asymmetric random walks on the cycle graph, with uniform killing. We show that this model has a remarkable exact solvability, despite the fact that it is…

Probability · Mathematics 2021-04-13 Josué Corujo

It has been observed that an interesting class of non-Gaussian stationary processes is obtained when in the harmonics of a signal with random amplitudes and phases, frequencies can also vary randomly. In the resulting models, the…

Probability · Mathematics 2019-11-19 Anastassia Baxevani , Krzysztof Podgórski

Rao and Teh (2012, 2013) introduced an efficient MCMC algorithm for sampling from the posterior distribution of a hidden Markov jump process. The algorithm is based on the idea of sampling virtual jumps. In the present paper we show that…

Computation · Statistics 2016-06-28 Błażej Miasojedow , Wojcieh Niemiro