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Test of misspecification with application to negative binomial distribution

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  • K. Chua
  • S. Ong

Abstract

A misspecification test based directly on Bartlett’s First Identity is examined. This test is exemplified by the negative binomial distribution. A Monte Carlo simulation study has been conducted, in the context of testing distributional misspecification, and the performance of the proposed test has been benchmarked with some goodness-of-fit tests based on the empirical distribution function. The results suggest that the proposed test is viable in terms of computational speed and statistical power, and has the advantage that complications arising from the use of the covariance matrix in White’s information matrix test are avoided. Copyright Springer-Verlag 2013

Suggested Citation

  • K. Chua & S. Ong, 2013. "Test of misspecification with application to negative binomial distribution," Computational Statistics, Springer, vol. 28(3), pages 993-1009, June.
    • Handle: RePEc:spr:compst:v:28:y:2013:i:3:p:993-1009
    DOI: 10.1007/s00180-012-0345-x
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    References listed on IDEAS

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    1. Ong, S.H. & Lee, Wen-Jau, 2008. "Computer generation of negative binomial variates by envelope rejection," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4175-4183, May.
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    7. Famoye, Felix, 2000. "Goodness-of-fit tests for generalized logarithmic series distribution," Computational Statistics & Data Analysis, Elsevier, vol. 33(1), pages 59-67, March.
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