SMOOTH TESTS FOR THE BIVARIATE POISSON DISTRIBUTION |
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Authors: | J.C.W. Rayner D.J. Best |
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Affiliation: | Dept of Applied Statistics, University of Wollongong, Northfields Ave, Wollongong, NSW 2522, Australia.;Biometrics Unit, CSIRO Food Research Laboratory, PO Box 52, North Ryde, NSW 2113, Australia. |
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Abstract: | A theorem of Rayner & Best (1989) is generalised to permit the construction of smooth tests of goodness of fit without requiring a set of orthonormal functions on the hypothesised distribution. This result is used to construct smooth tests for the bivariate Poisson distribution. The test due to Crockett (1979) is similar to a smooth test that assesses the variance structure under the bivariate Poisson model; the test due to Loukas & Kemp (1986) is related to a smooth test that seeks to detect a particular linear relationship between the variances and covariance under the bivariate Poisson model. Using focused smooth tests may be more informative than using previously suggested tests. The distribution of the Loukas & Kemp (1986) statistic is not well approximated by the x2distribution for larger correlations, and a revised statistic is suggested. |
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Keywords: | Crockett's test goodness of fit Hermite alternatives index of dispersion test score statistics. |
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