Improved Small Sample Model Selection Procedures

Maxwell L. King, Catherine Scipione Forbes and Alan Morgan

No 267920, Department of Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: This paper is concerned with model selection based on penalized maximized log likelihood functions. Its main emphasis is on how these penalties might be chosen in small samples to give good statistical properties. We explore how some of the more successful principles and practices in hypothesis testing can be used to improve the properties of these model selection procedures. This leads to choosing the penalties in order to control probabilities of different models being selected. Various ways this can be achieved using simulation methods are discussed and a computer algorithm is outlined. Some illustrative Monte Carlo simulations are also reported.

Keywords: Research; Methods/Statistical; Methods (search for similar items in EconPapers)
Pages: 22
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Persistent link: https://EconPapers.repec.org/RePEc:ags:monebs:267920

DOI: 10.22004/ag.econ.267920

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