AbstractA coupling method is used to obtain the explicit upper and lower bounds for convergence rates in strong ergodicity for Markov processes. For one-dimensional diffusion processes and birth–death processes, these bounds are sharp in the sense that the upper one and the lower one only differ in a constant
AbstractThe aim of this paper is to establish a strong law of large numbers for the bivariate functi...
Improved rates of convergence for ergodic Markov chains and relaxed conditions for them, as well as ...
International audienceLet $P$ be a Markov kernel on a measurable space $\mathbb{X}$ and let $V:\math...
AbstractA coupling method is used to obtain the explicit upper and lower bounds for convergence rate...
AbstractThis paper discusses quantitative bounds on the convergence rates of Markov chains, under co...
AbstractFor finite Markov chains the eigenvalues of P can be used to characterize the chain and also...
AbstractFor Lp convergence rates of a time homogeneous Markov process, sufficient conditions are giv...
We study the ergodic behaviour of a discrete-time process X which is a Markov chain in a stationary ...
AbstractWe provide a condition in terms of a supermartingale property for a functional of the Markov...
Strong invariance principles describe the error term of a Brownian approximation of the partial sums...
We study the relationship between two classical approaches for quantitative ergodic properties : the...
To appear in Advances in Applied Probability, Vol 46(4), 2014International audienceLet $\{X_n\}_{n\i...
AbstractQuantitative geometric rates of convergence for reversible Markov chains are closely related...
We provide a condition for f-ergodicity of strong Markov processes at a subgeometric rate. This cond...
For Lp convergence rates of a time homogeneous Markov process, sufficient conditions are given in te...
AbstractThe aim of this paper is to establish a strong law of large numbers for the bivariate functi...
Improved rates of convergence for ergodic Markov chains and relaxed conditions for them, as well as ...
International audienceLet $P$ be a Markov kernel on a measurable space $\mathbb{X}$ and let $V:\math...
AbstractA coupling method is used to obtain the explicit upper and lower bounds for convergence rate...
AbstractThis paper discusses quantitative bounds on the convergence rates of Markov chains, under co...
AbstractFor finite Markov chains the eigenvalues of P can be used to characterize the chain and also...
AbstractFor Lp convergence rates of a time homogeneous Markov process, sufficient conditions are giv...
We study the ergodic behaviour of a discrete-time process X which is a Markov chain in a stationary ...
AbstractWe provide a condition in terms of a supermartingale property for a functional of the Markov...
Strong invariance principles describe the error term of a Brownian approximation of the partial sums...
We study the relationship between two classical approaches for quantitative ergodic properties : the...
To appear in Advances in Applied Probability, Vol 46(4), 2014International audienceLet $\{X_n\}_{n\i...
AbstractQuantitative geometric rates of convergence for reversible Markov chains are closely related...
We provide a condition for f-ergodicity of strong Markov processes at a subgeometric rate. This cond...
For Lp convergence rates of a time homogeneous Markov process, sufficient conditions are given in te...
AbstractThe aim of this paper is to establish a strong law of large numbers for the bivariate functi...
Improved rates of convergence for ergodic Markov chains and relaxed conditions for them, as well as ...
International audienceLet $P$ be a Markov kernel on a measurable space $\mathbb{X}$ and let $V:\math...