Bias Correction in Generalized Nonlinear Models with Dispersion Covariates

We derive general formulae for the second-order biases of maximum likelihood estimates of the parameters in generalized nonlinear models with dispersion covariates. This result generalizes previous work by Botter and Cordeiro ( 1998 ) and Cordeiro and McCullagh ( 1991 ). The practical use of such bi...

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Bibliographic Details
Published in:	Communications in statistics. Theory and methods Vol. 37; no. 14; pp. 2219 - 2225
Main Authors:	Cordeiro, Gauss M., Toyama Udo, Margareth C.
Format:	Journal Article
Language:	English
Published:	Philadelphia, PA Taylor & Francis Group 27-05-2008 Taylor & Francis
Subjects:	Bias correction Dispersion parameter Exact sciences and technology General topics Generalized nonlinear model Mathematics Maximum likelihood Precision parameter Primary 62J05 Probability and statistics Sciences and techniques of general use Secondary 62E20 Statistics Bias Secondary 62E20 Primary 62J05 Covariate Statistical simulation Statistical method Bias correction Non linear model Dispersion measure Maximum likelihood Generalized nonlinear model Biased estimation Dispersion parameter Precision parameter
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Summary:	We derive general formulae for the second-order biases of maximum likelihood estimates of the parameters in generalized nonlinear models with dispersion covariates. This result generalizes previous work by Botter and Cordeiro ( 1998 ) and Cordeiro and McCullagh ( 1991 ). The practical use of such bias corrections is illustrated in a simulation study.
ISSN:	0361-0926 1532-415X
DOI:	10.1080/03610920801931895