Bayesian Subset Model Selection for Time Series

N. K. Unnikrishnan

Journal of Time Series Analysis, 2004, vol. 25, issue 5, 671-690

Abstract: Abstract. This paper considers the problem of subset model selection for time series. In general, a few lags which are not necessarily continuous, explain lag structure of a time‐series model. Using the reversible jump Markov chain technique, the paper develops a fully Bayesian solution for the problem. The method is illustrated using the self‐exciting threshold autoregressive (SETAR), bilinear and AR models. The Canadian lynx data, the Wolfe's sunspot numbers and Series A of Box and Jenkins (1976) are analysed in detail.

Date: 2004
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https://doi.org/10.1111/j.1467-9892.2004.01874.x

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Persistent link: https://EconPapers.repec.org/RePEc:bla:jtsera:v:25:y:2004:i:5:p:671-690

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