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AIC and Large Samples

Kieseppä, I. A. (2002) AIC and Large Samples. [Preprint]

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    Abstract

    I discuss the behavior of the Akaike Information Criterion in the limit when the sample size grows. I show the falsity of the claim made recently by Stanley Mulaik in Philosophy of Science that AIC would not distinguish between saturated and other correct factor analytic models in this limit. I explain the meaning and demonstrate the validity of the familiar, more moderate criticism that AIC is not a consistent estimator of the number of parameters of the smallest correct model. I also give a short explanation why this feature of AIC is compatible with the motives of using it.


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    Item Type: Preprint
    Keywords: Probability Statistics, Confirmation/Induction, Model Selection Criteria
    Conferences and Volumes: [2002] Philosophy of Science Assoc. 18th Biennial Mtg - PSA 2002: Contributed Papers (Milwaukee, WI; 2002) > PSA 2002 Contributed Papers
    Depositing User: Program Committee
    Date Deposited: 23 Mar 2003
    Last Modified: 07 Oct 2010 11:11
    Item ID: 1079
    URI: http://philsci-archive.pitt.edu/id/eprint/1079

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