collaborators

5 papers

math.PR2025

Sharp Mixing Rates for Markov Chains on General Spaces with Unbounded Random Environments

Attila Lovas, Miklós Rásonyi, Lionel Truquet

We consider Markov chains on general state spaces in stationary random environment which are defined by a random mapping that is contractive up to a bounded perturbation. We prove…

math.PR2025

Mixing properties of some Markov chains models in random environments

Attila Lovas, Lionel Truquet

Markov chains in random environments (MCREs) have recently attracted renewed interest, as these processes naturally arise in many applications, such as econometrics and machine lea…

math.ST2024

Mixing properties of nonstationary multivariate count processes

Zinsou Max Debaly, Michael H. Neumann, Lionel Truquet

We prove absolute regularity (-mixing) for nonstationary and multivariate versions of two popular classes of integer-valued processes. We show how this result can be used to pr…

math.ST2024

Time series on compact spaces, with an application to dynamic modeling of relative abundance data in Ecology

Guillaume Franchi, Lionel Truquet

Motivated by the dynamic modeling of relative abundance data in ecology, we introduce a general approach to model stationary Markovian or non Markovian time series on (relatively)…

math.ST2024

Theory and inference for multivariate autoregressive binary models with an application to absence-presence data in ecology

Guillaume Franchi, Lionel Truquet

We introduce a general class of autoregressive models for studying the dynamic of multivariate binary time series with stationary exogenous covariates. Using a high-level set of as…