Resumen de An MM-algorithm for a class of overdispersed regression models

Célestin C. Kokonendji , Simplice Dossou-Gbété, C. Demétrio

• 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