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Regressão Gama (GLM)×Regressão Quantílica×
ÁreaEstatísticaEconometria
FamíliaRegression modelRegression model
Ano de origem19891978
Autor originalMcCullagh & Nelder (GLM framework)Koenker & Bassett
TipoGeneralized linear modelConditional quantile regression
Fonte seminalMcCullagh, P. & Nelder, J. A. (1989). Generalized Linear Models (2nd ed.). Chapman and Hall. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
Outros nomesgamma GLM, gamma generalized linear model, Gamma Regresyonu (GLM)conditional quantile regression, regression quantiles, Kantil Regresyon
Relacionados45
ResumoGamma 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.Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.
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ScholarGateComparar métodos: Gamma Regression · Quantile Regression. Recuperado em 2026-06-18 de https://scholargate.app/pt/compare