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SMOOTH TESTS FOR THE BIVARIATE POISSON DISTRIBUTION
Author(s) -
Rayner J.C.W.,
Best D.J.
Publication year - 1995
Publication title -
australian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 41
eISSN - 1467-842X
pISSN - 0004-9581
DOI - 10.1111/j.1467-842x.1995.tb00656.x
Subject(s) - bivariate analysis , mathematics , poisson distribution , statistics , goodness of fit , multivariate normal distribution , test statistic , covariance , statistic , statistical hypothesis testing , multivariate statistics
Summary 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 x 2 distribution for larger correlations, and a revised statistic is suggested.