Statistical analysis of multivariate discrete-valued time series

Konstantinos Fokianos, Roland Fried, Yurij S. Kharin, Valeriy Voloshko

Abstract: This work gives an overview of statistical analysis for some models for multivariate discrete-valued (MDV) time series. We present observation-driven models and models based on higher-order Markov chains. Several extensions are highlighted including non-stationarity, network autoregressions, conditional non-linear autoregressive models, robust estimation, random fields and spatio-temporal models.