An MM-algorithm for a class of overdispersed regression models

Autores: Célestin C. Kokonendji , Simplice Dossou-Gbété, C. Demétrio
Localización: Ninth international conference Zaragoza-Pau on applied mathematics and statistics: Jaca (Spain). September 19-21, 2005 / coord. por Monique Madaune-Tort , 2006, ISBN 84-7733-871-X, págs. 229-236
Idioma: inglés
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Resumen
- The aim of the paper is to provide an algorithm for the computation of the regression parameters estimation in the framework of generalized linear model for count data. Regression parameters are estimated through the minimization of the quasi-likelihood and the main feature of that algorithm, which relies on MM method, is not to resort to matrix inversion as in Newton-Raphson algorithm and Fisher-Scoring method