Persistent random walks, variable length Markov chains and piecewise deterministic Markov processes

In this section we study a PDMP on R 2 × { 0, 1 } such that the strong bracket condition holds everywhere except on Γ and which may have one or three ergodic invariant

The goal of the present paper is to complete these investigations by establishing local limit theorems for random walks defined on finite Markov chains and conditioned to

ρ-mixing case (Proof of Application 1 of Section 1). 4-5] for additive functionals. Exten- sion to general MRW is straightforward. Then Application 1 of Section 1 follows from

La carte ExpoPass des Musées d’art et d’histoire offre un accès libre à toutes les expositions temporaires du Musée d’art et d’histoire, du Musée Rath, du Cabinet

L’utilisation des méthodes numériques de discrétisation pour la résolution des équations mathématiques établies, consiste à ramener la résolution des EDPs dans le

In Figure 1, the dynamical system together with Lebesgue measure on [0, 1] define a probabilistic source that corresponds to the stationary VLMC defined by the drawn

We give a short overview of recent results on a specific class of Markov process: the Piecewise Deterministic Markov Processes (PDMPs).. We first recall the definition of

Keywords: second order Markov chains, trajectorial reversibility, spectrum of non-reversible Markov kernels, spectral gap, improvement of speed of convergence, discrete