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Bias correction of the Akaike information criterion in factor analysis

Listed author(s):
  • Ogasawara, Haruhiko
Registered author(s):

    The higher-order asymptotic bias for the Akaike information criterion (AIC) in factor analysis or covariance structure analysis is obtained when the parameter estimators are given by the Wishart maximum likelihood. Since the formula of the exact higher-order bias is complicated, simple approximations which do not include unknown parameter values are obtained. Numerical examples with simulations show that the approximations are reasonably similar to their corresponding exact asymptotic values and simulated values. Simulations for model selection give consistently improved results by the approximate correction of the higher-order bias for the AIC over the usual AIC.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0047259X16300161
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    Article provided by Elsevier in its journal Journal of Multivariate Analysis.

    Volume (Year): 149 (2016)
    Issue (Month): C ()
    Pages: 144-159

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    Handle: RePEc:eee:jmvana:v:149:y:2016:i:c:p:144-159
    DOI: 10.1016/j.jmva.2016.04.003
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    17. Ogasawara, Haruhiko, 2015. "Asymptotic cumulants of some information criteria," ビジネス創造センターディスカッション・ペーパー (Discussion papers of the Center for Business Creation) 10252/5446, Otaru University of Commerce.
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