Forecasting in INAR(1) Model

In this work we consider the problem of forecasting integer-valued time series, modelled by the INAR(1) process introduced by McKenzie (1985) and Al-Osh and Alzaid (1987). The theoretical properties and practical applications of INAR and related processes have been discussed extensively in the liter...

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Bibliographic Details
Published inRevstat Vol. 7; no. 1
Main Authors Nélia Silva, Isabel Pereira, M. Eduarda Silva
Format Journal Article
LanguageEnglish
Published Instituto Nacional de Estatística | Statistics Portugal 01.04.2009
Subjects
Bayesian prediction
INAR models
integer prediction
Markov Chain Monte Carlo algorithm
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Summary:In this work we consider the problem of forecasting integer-valued time series, modelled by the INAR(1) process introduced by McKenzie (1985) and Al-Osh and Alzaid (1987). The theoretical properties and practical applications of INAR and related processes have been discussed extensively in the literature but there is still some discussion on the problem of producing coherent, i.e. integer-valued, predictions. Here Bayesian methodology is used to obtain point predictions as well as confidence intervals for future values of the process. The predictions thus obtained are compared with their classic counterparts. The proposed approaches are illustrated with a simulation study and a real example.
ISSN:1645-6726
2183-0371
DOI:10.57805/revstat.v7i1.77