Abstract

Addresses a class of statistical models that generalizes classical linear models-extending them to include many other models useful in statistical analysis. Incorporates numerous exercises, both theoretical and data-analytic Discusses quasi-likelihood functions and estimating equations, models for dispersion effect, components of dispersion, and conditional likelihoods Holds particular interest for statisticians in medicine, biology, agriculture, social science, and engineering

Keywords

Generalized linear modelApplied mathematicsMathematicsEconometrics

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Publication Info

Year
1993
Type
article
Volume
88
Issue
422
Pages
698-698
Citations
4940
Access
Closed

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Terry M. Therneau, Peter McCullagh, J. A. Nelder (1993). Generalized Linear Models (2nd ed.).. Journal of the American Statistical Association , 88 (422) , 698-698. https://doi.org/10.2307/2290358

Identifiers

DOI
10.2307/2290358