On Categorical Time Series Models With Covariates - Archive ouverte HAL Accéder directement au contenu
Pré-Publication, Document De Travail Année : 2017

On Categorical Time Series Models With Covariates

Résumé

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-type recursive equation. We improve considerably upon the existing results related to stationarity and ergodicity conditions of such models. Proofs are based on theory developed for chains with complete connections. This approach is based on a useful coupling technique which is utilized for studying ergodicity of more general finite-state stochastic processes. Such processes generalize finite-state Markov chains by assuming infinite order models of past values. For finite order Markov chains, we also discuss ergodicity properties when some strongly exogenous covariates are considered in the dynamics of the process.

Dates et versions

hal-01612190 , version 1 (06-10-2017)

Identifiants

Citer

Konstantinos Fokianos, Lionel Truquet. On Categorical Time Series Models With Covariates. 2017. ⟨hal-01612190⟩
210 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More