Selecting nonlinear time series models using information criteria

This article considers the problem of selecting among competing nonlinear time series models by using complexity-penalized likelihood criteria. An extensive simulation study is undertaken to assess the small-sample performance of several popular criteria in selecting among nonlinear autoregressive models belonging to some families that have been popular with practitioners. Copyright 2009 Blackwell Publishing Ltd

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Year of publication:	2009
Authors:	Psaradakis, Zacharias ; Sola, Martin ; Spagnolo, Fabio ; Spagnolo, Nicola
Published in:	Journal of Time Series Analysis. - Wiley Blackwell, ISSN 0143-9782. - Vol. 30.2009, 4, p. 369-394
Publisher:	Wiley Blackwell

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Extent:	text/html
Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005005179