Title of article :
New inference procedures for generalized Poisson distributions
Author/Authors :
Simos G. Meintanis، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2008
Pages :
12
From page :
751
To page :
762
Abstract :
A common feature for compound Poisson and Katz distributions is that both families may be viewed as generalizations of the Poisson law. In this paper, we present a unified approach in testing the fit to any distribution belonging to either of these families. The test involves the probability generating function, and it is shown to be consistent under general alternatives. The asymptotic null distribution of the test statistic is obtained, and an effective bootstrap procedure is employed in order to investigate the performance of the proposed test with real and simulated data. Comparisons with classical methods based on the empirical distribution function are also included.
Keywords :
Empirical probability generating function , Katz laws , Compound Poisson distribution , goodness-of-fittest
Journal title :
JOURNAL OF APPLIED STATISTICS
Serial Year :
2008
Journal title :
JOURNAL OF APPLIED STATISTICS
Record number :
712228
Link To Document :
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