2021/03/14 by Fokianos, Konstantinos · 1 citation
#FOS: Computer and information sciences #Methodology (stat.ME)
paper · doi:10.48550/arxiv.2103.08028
We review autoregressive models for the analysis of multivariate count time series. In doing so, we discuss the choice of a suitable distribution for a vectors of count random variables. This review focus on three main approaches taken for multivariate count time series analysis: (a) integer autoregressive processes, (b) parameter-driven models and (c) observation-driven models. The aim of this work is to highlight some recent methodological developments and propose some potentially useful research topics.