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 Forecasting in INAR(1) model
Please use this identifier to cite or link to this item http://hdl.handle.net/10773/4428

title: Forecasting in INAR(1) model
authors: Silva, N
Pereira, I
Silva, ME
keywords: INAR models
Bayesian prediction
integer prediction
Markov Chain Monte Carlo algorithm
issue date: 2009
publisher: Instituto Nacional de Estatística
abstract: 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.
URI: http://hdl.handle.net/10773/4428
ISSN: 1645-6726
publisher version/DOI: http://www.ine.pt/revstat/pdf/rs090108.pdf
source: REVSTAT-STATISTICAL JOURNAL
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