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Conditional tests for homogeneity of zero-inflated Poisson and Poisson-hurdle distributions

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  • Bedrick, Edward J.
  • Hossain, Anwar

Abstract

We develop two conditional tests for homogeneity of zero-inflated Poisson (ZIP) and Poisson-hurdle distributions. A Monte Carlo method is proposed for approximating the reference distributions of these tests. The techniques are applied to two examples.

Suggested Citation

  • Bedrick, Edward J. & Hossain, Anwar, 2013. "Conditional tests for homogeneity of zero-inflated Poisson and Poisson-hurdle distributions," Computational Statistics & Data Analysis, Elsevier, vol. 61(C), pages 99-106.
    • Handle: RePEc:eee:csdana:v:61:y:2013:i:c:p:99-106
    DOI: 10.1016/j.csda.2012.11.009
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    1. Chris Corcoran & Louise Ryan & Pralay Senchaudhuri & Cyrus Mehta & Nitin Patel & Geert Molenberghs, 2001. "An Exact Trend Test for Correlated Binary Data," Biometrics, The International Biometric Society, vol. 57(3), pages 941-948, September.
    2. Gupta, Pushpa L. & Gupta, Ramesh C. & Tripathi, Ram C., 1996. "Analysis of zero-adjusted count data," Computational Statistics & Data Analysis, Elsevier, vol. 23(2), pages 207-218, December.
    3. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    4. Martin Ridout & John Hinde & Clarice G. B. Demétrio, 2001. "A Score Test for Testing a Zero‐Inflated Poisson Regression Model Against Zero‐Inflated Negative Binomial Alternatives," Biometrics, The International Biometric Society, vol. 57(1), pages 219-223, March.
    5. Karen E. Han & Paul J. Catalano & Pralay Senchaudhuri & Cyrus Mehta, 2004. "Exact Analysis of Dose Response for Multiple Correlated Binary Outcomes," Biometrics, The International Biometric Society, vol. 60(1), pages 216-224, March.
    6. D. Böhning & E. Dietz & P. Schlattmann & L. Mendonça & U. Kirchner, 1999. "The zero‐inflated Poisson model and the decayed, missing and filled teeth index in dental epidemiology," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 162(2), pages 195-209.
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    Cited by:

    1. Liu, Yin & Tian, Guo-Liang, 2015. "Type I multivariate zero-inflated Poisson distribution with applications," Computational Statistics & Data Analysis, Elsevier, vol. 83(C), pages 200-222.
    2. Wang, Chunlin & Marriott, Paul & Li, Pengfei, 2017. "Testing homogeneity for multiple nonnegative distributions with excess zero observations," Computational Statistics & Data Analysis, Elsevier, vol. 114(C), pages 146-157.

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