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On inference for threshold autoregressive models
Journal article   Peer reviewed

On inference for threshold autoregressive models

Osnat Stramer and Yu-Jau Lin
Test (Madrid, Spain), Vol.11(1), pp.55-71
06/2002
DOI: 10.1007/BF02595729

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Abstract

We provide a complete Bayesian method for analyzing a threshold autoregressive (TAR) model when the order of the model is unknown. Our approach is based on a version (Godsill (2001)) of the reversible jump algorithm of Green (1995), and the method for estimating marginal likelihood from the Metropolis-Hasting algorithm by Chib and Jeliazkov (2001). We illustrate our results with simulated data and the Wolfe's sunspot data set.

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