Please use this identifier to cite or link to this item: http://hdl.handle.net/11718/9998
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dc.contributor.authorBanerjee, Tathagata
dc.contributor.authorPaul, Sudhir
dc.contributor.authorBalsuriya, Uditha
dc.date.accessioned2005-10-26T11:52:30Z
dc.date.available2005-10-26T11:52:30Z
dc.date.copyright2005
dc.date.issued2005-10-26T11:52:30Z
dc.identifier.citationBanerjee, Tathagata et al. (April 2005), Fisher information matrix of the Dirichlet-multinomial distribution, Biometrical Journal, Wiley Interscience, Vol. 47(2), Pp. 230-236
dc.identifier.urihttp://hdl.handle.net/11718/9998
dc.description.abstractIn this paper we derive explicit expressions for the elements of the exact Fisher information matrix of the Dirichlet-multinomial distribution. We show that exact calculation is based on the beta-binomial probability function rather than that of the Dirichlet-multinomial and this makes the exact calculation quite easy. The exact results are expected to be useful for the calculation of standard errors of the maximum likelihood estimates of the beta-binomial parameters and those of the Dirichlet-multinomial parameters for data that arise in practice in toxicology and other similar fields. Standard errors of the maximum likelihood estimates of the beta-binomial parameters and those of the Dirichlet-multinomial parameters, based on the exact and the asymptotic Fisher information matrix based on the Dirichlet distribution, are obtained for a set of data from Haseman and Soares (1976), a dataset from Mosimann (1962) and a more recent dataset from Chen, Kodell, Howe and Gaylor (1991). There is substantial difference between the standard errors of the estimates based on the exact Fisher information matrix and those based on the asymptotic Fisher information matrix.
dc.language.isoenen
dc.subjectApproximate Fisher information matrixen
dc.subjectBeta-binomial distributionen
dc.subjectDirichlet-multinomial distributionen
dc.subjectExact Fisher information matrixen
dc.subjectMaximum likelihood estimatesen
dc.titleFisher information matrix of the Dirichlet-multinomial distributionen
dc.typeArticleen
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