File Name: mccullagh and nelder 1989 .zip
Skip to search form Skip to main content You are currently offline. Some features of the site may not work correctly. DOI: Nelder and R. Nelder , R. Wedderburn Published Mathematics. JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive.
Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated. Consistency and asymptotic normality of the maximum likelihood estimator in a zero-inflated generalized Poisson regression. Poisson regression models for count variables have been utilized in many applications. However, in many problems overdispersion and zeroinflation occur. We study in this paper regression models based on the generalized Poisson distribution Consul
The data contains values on the number of reported accidents for ships belonging to a company over a given time period. Mccullagh and nelder who show that if the distribution of. Lwin 36 symmetric multivariate and related distributions k. Nelder, which ensures that the response surface is invariant under scaling and translation of the explanatory variables in the model. Figure 6 is a part where the estimate of the variance of u 0j i. There are already several excellent books on this topic.
Monographs on Statistics and. Applied Probability Generalized. Linear Models. SECOND EDITION. P. McCullagh and. J.A. Nelder FRS. 2 Chapman and Hall.
The class of generalized linear models was introduced in by Nelder and Wedderburn  Hardin and Hilbe  and McCullagh and Nelder  give more comprehensive treatments. McCullagh, John A. Use the link below to share a full-text version of this article with your friends and colleagues. Learn more. Volume 29Issue 2.
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Scientific Research An Academic Publisher. McCullagh, P. ABSTRACT: This paper presents a new approach to identify and estimate the dispersion parameters for bivariate, trivariate and multivariate correlated binary data, not only with scalar value but also with matrix values.
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