Journal
SORT-STATISTICS AND OPERATIONS RESEARCH TRANSACTIONS
Volume 43, Issue 2, Pages 355-384Publisher
INST ESTADISTICA CATALUNYA-IDESCAT
DOI: 10.2436/20.8080.02.92
Keywords
INAR; negative binomial thinning; random states; time series of count; non-stationary process
Funding
- [MNTR 174026]
- [MNTR 174013]
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In this article, we consider two univariate random environment integer-valued autoregressive processes driven by the same hidden process. A model of this kind is capable of describing two correlated non-stationary counting time series using its marginal variable parameter values. The properties of the model are presented. Some parameter estimators are described and implemented on the simulated time series. The introduction of this bivariate integer-valued autoregressive model with a random environment is justified at the end of the paper, where its real-life data-fitting performance was checked and compared to some other appropriate models. The forecasting properties of the model are tested on a few data sets, and forecasting errors are discussed through the residual analysis of the components that comprise the model.
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