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Poisson- og negativ binomial regresjon×Kvantilregresjon×
FagfeltØkonometriØkonometri
FamilieRegression modelRegression model
Opprinnelsesår19981978
OpphavspersonCameron & Trivedi (textbook treatment); Hilbe (negative binomial)Koenker & Bassett
TypeGeneralized linear model for count dataConditional quantile regression
Opprinnelig kildeCameron, A. C. & Trivedi, P. K. (1998). Regression Analysis of Count Data. Cambridge University Press. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
Aliascount regression, log-linear count model, negative binomial regression, Poisson / Negatif Binom Regresyonconditional quantile regression, regression quantiles, Kantil Regresyon
Relaterte45
SammendragPoisson 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.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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ScholarGateSammenlign metoder: Poisson Regression · Quantile Regression. Hentet 2026-06-17 fra https://scholargate.app/no/compare