4 citations · 11 across the 16 of their papers we have counts for
15 papers · 1 filter
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…
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 pro…
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)…
Strong mixing properties of discrete-valued time series with exogenous covariates
Lionel Truquet
We derive strong mixing conditions for many existing discrete-valued time series models that include exogenous covariates in the dynamic. Our main contribution is to study how a mi…
Stationarity and ergodic properties for some observation-driven models in random environments
Paul Doukhan, Michael H. Neumann, Lionel Truquet
The first motivation of this paper is to study stationarity and ergodic properties for a general class of time series models defined conditional on an exogenous covariates process.…
Stationarity and Moment Properties of some Multivariate Count Autoregressions
Zinsou Max Debaly, Lionel Truquet
We study stationarity and moments properties of some count time series models from contraction and stability properties of iterated random maps. Both univariate and multivariate pr…
Iterations of dependent random maps and exogeneity in nonlinear dynamics
Max Zinsou Debaly, Lionel Truquet
We discuss existence and uniqueness of stationary and ergodic nonlinear autoregressive processes when exogenous regressors are incorporated in the dynamic. To this end, we consider…
Coupling and perturbation techniques for categorical time series
Lionel Truquet
We present a general approach for studying autoregressive categorical time series models with dependence of infinite order and defined conditional on an exogenous covariate process…
On Categorical Time Series Models With Covariates
Konstantinos Fokianos, Lionel Truquet
We study the problem of stationarity and ergodicity for autoregressive multinomial logistic time series models which possibly include a latent process and are defined by a GARCH-ty…
Efficient semiparametric estimation in time-varying regression models
Lionel Truquet
We study semiparametric inference in some linear regression models with time-varying coefficients, dependent regressors and dependent errors. This problem, which has been considere…
A perturbation analysis of some Markov chains models with time-varying parameters
Lionel Truquet
We study some regularity properties in locally stationary Markov models which are fundamental for controlling the bias of nonparametric kernel estimators. In particular, we provide…
Root-n consistent estimation of the marginal density in some time series models
Lionel Truquet
In this paper, we consider the problem of estimating the marginal density in some nonlinear autoregressive time series models for which the conditional mean and variance have a par…
Local stationarity and time-inhomogeneous Markov chains
Lionel Truquet
In this paper, we study a notion of local stationarity for discrete time Markov chains which is useful for applications in statistics. In the spirit of some locally stationary proc…
A nonparametric test for Cox processes
Benoît Cadre, Gaspar Massiot, Lionel Truquet
In a functional setting, we propose two test statistics to highlight the Poisson nature of a Cox process when n copies of the process are available. Our approach involves a compari…
Parameter stability and semiparametric inference in time-varying ARCH models
Lionel Truquet
In this paper, we develop a complete methodology for detecting time-varying/non time-varying parameters in ARCH processes. For this purpose, we estimate and test various semiparame…