We are investigating Markov process expectations for large time of the form $\exp(TF(L_T))$, where $L_T$ is the empirical measure of a uniformly ergodic Markov process and $F$ is a smooth functional. Such expressions are evaluated to a factor which converges to 1. In contrast to earlier work on the subject, it is not assumed that the process is reversible
A large deviations principle is established for the joint law of the empirical measure and the flow ...
This thesis is devoted to the studies of two themes : large deviations of the kernel density estmato...
AbstractIn this paper, we prove the large deviation principle (LDP) for the occupation measures of n...
Abstract. Let LT be the empirical measrue of a uniformly ergodic nonreversible Markov process on a c...
Abstract. Let Ln be the empirical measure of a uniformly er-godic nonreversible Markov chain on a co...
. We combine the Donsker and Varadhan large deviation principle (l.d.p.) for the occupation measure ...
In this paper we continue the investigation of the spectral theory and exponential asymptotics of pr...
A large deviations principle is established for the joint law of the empirical measure and the flow ...
To sample from distributions in high dimensional spaces or finite large sets di-rectly is not feasib...
A large deviations principle is established for the joint law of the empirical measure and the flow ...
We prove the large deviation principle for empirical estimators of stationary distributions of semi-...
We prove the large deviation principle for empirical estimators of stationary distributions of semi-...
We prove the large deviation principle for empirical estimators of stationary distributions of semi-...
We prove the large deviation principle for empirical estimators of stationary distributions of semi-...
We prove the large deviation principle for empirical estimators of stationary distributions of semi-...
A large deviations principle is established for the joint law of the empirical measure and the flow ...
This thesis is devoted to the studies of two themes : large deviations of the kernel density estmato...
AbstractIn this paper, we prove the large deviation principle (LDP) for the occupation measures of n...
Abstract. Let LT be the empirical measrue of a uniformly ergodic nonreversible Markov process on a c...
Abstract. Let Ln be the empirical measure of a uniformly er-godic nonreversible Markov chain on a co...
. We combine the Donsker and Varadhan large deviation principle (l.d.p.) for the occupation measure ...
In this paper we continue the investigation of the spectral theory and exponential asymptotics of pr...
A large deviations principle is established for the joint law of the empirical measure and the flow ...
To sample from distributions in high dimensional spaces or finite large sets di-rectly is not feasib...
A large deviations principle is established for the joint law of the empirical measure and the flow ...
We prove the large deviation principle for empirical estimators of stationary distributions of semi-...
We prove the large deviation principle for empirical estimators of stationary distributions of semi-...
We prove the large deviation principle for empirical estimators of stationary distributions of semi-...
We prove the large deviation principle for empirical estimators of stationary distributions of semi-...
We prove the large deviation principle for empirical estimators of stationary distributions of semi-...
A large deviations principle is established for the joint law of the empirical measure and the flow ...
This thesis is devoted to the studies of two themes : large deviations of the kernel density estmato...
AbstractIn this paper, we prove the large deviation principle (LDP) for the occupation measures of n...