Forecasting in INAR(1) Model

Authors

  • Nélia Silva Universidade de Aveiro
  • Isabel Pereira Universidade de Aveiro
  • M. Eduarda Silva Universidade de Aveiro

DOI:

https://doi.org/10.57805/revstat.v7i1.77

Keywords:

INAR models, Bayesian prediction, integer prediction, Markov Chain Monte Carlo algorithm

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.

Published

2009-04-28

How to Cite

Silva , N., Pereira , I., & Silva , M. E. (2009). Forecasting in INAR(1) Model. REVSTAT-Statistical Journal, 7(1), 119–134. https://doi.org/10.57805/revstat.v7i1.77