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.
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The support received from the Research Professorship Program at Central Michigan University under the grant #22159 is gratefully acknowledged.
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Famoye, F. Bootstrap based tests for generalized negative binomial distribution. Computing 61, 359–369 (1998). https://doi.org/10.1007/BF02684385
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DOI: https://doi.org/10.1007/BF02684385