Multivariate Count Time Series Modelling
Methodology
2021-09-21 v2
Abstract
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.
Cite
@article{arxiv.2103.08028,
title = {Multivariate Count Time Series Modelling},
author = {Konstantinos Fokianos},
journal= {arXiv preprint arXiv:2103.08028},
year = {2021}
}