Bayesian analysis of change point problem in autoregressive model: a mixture model approach
format: Article | STATISTICA & APPLICAZIONI - 2009 - 2
This paper is a generalization of earlier studies by Venkatesan and Arumugam (2007) who considered the changes in the parameters of an autoregressive (AR) time series model in order to make Bayesian inference for the shift points and other parameters of a changing AR model. In this paper, the problem of gradual changes in the parameters of an AR model of pth order, through Bayesian mixture approach is considered. This model incorporates the beginning and end points of the interval of switch. Further, the Bayes estimates of the parameters are illustrated with the data generated from known model. Keywords: Autoregressive model, Bayesian estimation, Structural change, Mixture model, Numerical integration.