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Selecting nonlinear time series models using information criteria
Author(s) -
Psaradakis Zacharias,
Sola Martin,
Spagnolo Fabio,
Spagnolo Nicola
Publication year - 2009
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/j.1467-9892.2009.00614.x
Subject(s) - autoregressive model , mathematics , series (stratigraphy) , information criteria , nonlinear system , econometrics , sample (material) , time series , statistics , mathematical optimization , model selection , paleontology , physics , chemistry , chromatography , quantum mechanics , biology
. 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.