Bootstrap Based Tests for Generalized Negative Binomial Distribution

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Abstract

Goodness of fit test statistics based on the empirical distribution function (EDF) are considered for the generalized negative binomial distribution. The small sample levels of the tests are found to be very close to the nominal significance levels. For small sample sizes, the tests are compared with respect to their simulated power of detecting some alternative hypotheses against a null hypothesis of generalized negative binomial distribution. The discrete Anderson - Darling test is the most powerful among the EDF tests. Two numerical examples are used to illustrate the application of the goodness of fit tests.

Original languageEnglish
Pages (from-to)359-369
Number of pages11
JournalComputing (Vienna/New York)
Volume61
Issue number4
DOIs
StatePublished - 1998

Keywords

  • Empirical distribution function
  • Goodness of fit
  • Monte Carlo simulation
  • Power

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