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Negative Binomial Regression×Quantile Regression×
FachgebietÖkonometrieÖkonometrie
FamilieRegression modelRegression model
Entstehungsjahr20111978
UrheberHilbe (textbook treatment); generalized linear model frameworkKoenker & Bassett
TypGeneralized linear model for count dataConditional quantile regression
Wegweisende QuelleHilbe, J. M. (2011). Negative Binomial Regression (2nd ed.). Cambridge University Press. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
AliasnamenNB regression, NB2 regression, negatif binom regresyonuconditional quantile regression, regression quantiles, Kantil Regresyon
Verwandt45
ZusammenfassungNegative Binomial Regression is a generalized linear model for count outcomes that extends Poisson regression to handle overdispersion, where the variance of the counts exceeds their mean. Developed in the GLM tradition and treated in depth by Hilbe (2011), it adds a dispersion parameter so that inference stays valid when Poisson would understate the spread of the data.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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ScholarGateMethoden vergleichen: Negative Binomial Regression · Quantile Regression. Abgerufen am 2026-06-18 von https://scholargate.app/de/compare