Evaluating PcGets and RETINA as Automatic Model Selection Algorithms
AbstractThe paper describes two automatic model selection algorithms, RETINA and PcGets, briefly discussing how the algorithms work and what their performance claims are. RETINA's Matlab implementation of the code is explained, then the program is compared with PcGets on the data in Perez-Amaral, Gallo and White (2005, "Econometric Theory", Vol. 21, pp. 262-277), 'A Comparison of Complementary Automatic Modelling Methods: RETINA and PcGets', and Hoover and Perez (1999, "Econometrics Journal", Vol. 2, pp. 167-191), 'Data Mining Reconsidered: Encompassing and the General-to-specific Approach to Specification Search'. Monte Carlo simulation results assess the null and non-null rejection frequencies of the RETINA and PcGets model selection algorithms in the presence of nonlinear functions. Copyright 2005 Blackwell Publishing Ltd.
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Bibliographic InfoArticle provided by Department of Economics, University of Oxford in its journal Oxford Bulletin of Economics & Statistics.
Volume (Year): 67 (2005)
Issue (Month): s1 (December)
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