Compara mètodes

	Regressió Gamma (GLM)	Regressió de Poisson i binomial negativa
Camp	Estadística	Econometria
Família	Regression model	Regression model
Any d'origen	1989	1998
Autor original	McCullagh & Nelder (GLM framework)	Cameron & Trivedi (textbook treatment); Hilbe (negative binomial)
Tipus	Generalized linear model	Generalized linear model for count data
Font seminal	McCullagh, P. & Nelder, J. A. (1989). Generalized Linear Models (2nd ed.). Chapman and Hall.	Cameron, A. C. & Trivedi, P. K. (1998). Regression Analysis of Count Data. Cambridge University Press.
Àlies	gamma GLM, gamma generalized linear model, Gamma Regresyonu (GLM)	count regression, log-linear count model, negative binomial regression, Poisson / Negatif Binom Regresyon
Relacionats	4	4
Resum	Gamma regression is a generalized linear model that uses the gamma distribution to model a positive, right-skewed continuous outcome. Developed within the GLM framework of McCullagh and Nelder (1989), it is an alternative to ordinary linear regression for variables such as health-care costs, durations, and income.	Poisson regression is a generalized linear model for count outcomes — events tallied as non-negative integers such as hospital admissions, accidents, or article counts. It models the log of the expected count as a linear function of the predictors, and is developed in the standard count-data treatment of Cameron and Trivedi (1998); when the counts are over-dispersed, the closely related negative binomial model (Hilbe, 2011) is preferred.