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Generalized Linear Models: Software Implementation And The Structure Of A General Power-Link Based Glm Algorithm, Joseph Hilbe
Generalized Linear Models: Software Implementation And The Structure Of A General Power-Link Based Glm Algorithm, Joseph Hilbe
Joseph M Hilbe
Generalized linear modeling (GLM) is currently undergoing a renaissance. The number of software packages offering GLM capability grows each year and as a partial consequence one finds an increased number of research endeavors being modeled using GLM methodology. On the other hand, there have likewise been an increasing number of requests to vendors by users of statistical packages to include GLM facilities amid other offerings. The overall effect has been a near 300 percent increase in GLM programs over the past four years.
I shall discuss the nature of generalized linear models followed by an examination of how they have …
Log-Negative Binomial Regression As A Generalized Linear Model, Joseph Hilbe
Log-Negative Binomial Regression As A Generalized Linear Model, Joseph Hilbe
Joseph M Hilbe
The negative binomial (NB) is a member of the exponential family of discrete probability distributions. The nature of the distribution is itself well understood, but its contribution to regression modeling, in particular as a generalized linear model (GLM), has not been appreciated. The mathematical properties of the negative binomial are derived and GLM algorithms are developed for both the canonical and log form. Geometric regression is seen as an instance of the NB. The log forms of both may be effectively used to model types of POisson-overdispersed count data. A GLM-type algorithm is created for a general log-negative binomial regression …