On categorical time series models with covariates

DOI10.1016/j.spa.2018.09.012zbMath1431.62370arXiv1709.09372OpenAlexW2963701119MaRDI QIDQ2274307

Lionel Truquet, Konstantinos Fokianos

Publication date: 19 September 2019

Published in: Stochastic Processes and their Applications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1709.09372

zbMATH Keywords

ergodicityMarkov chaincouplingcategorical data

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Generalized linear models (logistic models) (62J12) Stationary stochastic processes (60G10)

Related Items (10)

Observation-driven models for discrete-valued time series ⋮ Variable length Markov chain with exogenous covariates ⋮ Modeling normalcy‐dominant ordinal time series: An application to air quality level ⋮ Stationarity and ergodic properties for some observation-driven models in random environments ⋮ Gaussian concentration bounds for stochastic chains of unbounded memory ⋮ A perturbation analysis of Markov chains models with time-varying parameters ⋮ Coupling and perturbation techniques for categorical time series ⋮ Statistical analysis of multivariate discrete-valued time series ⋮ Multivariate time series models for mixed data ⋮ ITERATIONS OF DEPENDENT RANDOM MAPS AND EXOGENEITY IN NONLINEAR DYNAMICS

Uses Software

• Fahrmeir

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