The SETAR model of Tong and Lim and advances in computation

Geweke, J

The SETAR model of Tong and Lim and advances in computation

Geweke, J

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Publication Type:: Chapter
Citation:: Exploration of a Nonlinear World: An Appreciation of Howell Tong's Contributions to Statistics, 2009, pp. 85 - 94
Issue Date:: 2009-01-01

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Field	Value	Language
dc.contributor.author	Geweke, J	en_US
dc.date.issued	2009-01-01	en_US
dc.identifier.citation	Exploration of a Nonlinear World: An Appreciation of Howell Tong's Contributions to Statistics, 2009, pp. 85 - 94	en_US
dc.identifier.isbn	9812836276	en_US
dc.identifier.isbn	9789812836274	en_US
dc.identifier.uri	http://hdl.handle.net/10453/7818
dc.description.abstract	© 2009 by World Scientific Publishing Co. Pte. Ltd. All rights reserved. This discussion revisits Tong and Lim's seminal 1980 paper on the SETAR model in the context of advances in computation since that time. Using the Canadian lynx data set from that paper, it compares exact maximum likelihood estimates with those in the original paper. It illustrates the application of Bayesian MCMC methods, developed in the intervening years, to this model and data set. It shows that SETAR is a limiting case of mixture of experts models and studies the application of one variant of those models to the lynx data set. The application is successful, despite the small size of the data set and the complexity of the model. Predicive likelihood ratios favor Tong and Lim's original model.	en_US
dc.relation.ispartof	Exploration of a Nonlinear World: An Appreciation of Howell Tong's Contributions to Statistics	en_US
dc.relation.isbasedon	10.1142/9789812836281_0006	en_US
dc.title	The SETAR model of Tong and Lim and advances in computation	en_US
dc.type	Chapter
utslib.for	010405 Statistical Theory	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Business/Economics Discipline
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

© 2009 by World Scientific Publishing Co. Pte. Ltd. All rights reserved. This discussion revisits Tong and Lim's seminal 1980 paper on the SETAR model in the context of advances in computation since that time. Using the Canadian lynx data set from that paper, it compares exact maximum likelihood estimates with those in the original paper. It illustrates the application of Bayesian MCMC methods, developed in the intervening years, to this model and data set. It shows that SETAR is a limiting case of mixture of experts models and studies the application of one variant of those models to the lynx data set. The application is successful, despite the small size of the data set and the complexity of the model. Predicive likelihood ratios favor Tong and Lim's original model.

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http://hdl.handle.net/10453/7818