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Tobitův regresní model s cenzurovanými daty×Negativně binomická regrese×
OborEkonometrieEkonometrie
RodinaRegression modelRegression model
Rok vzniku19582011
TvůrceJames TobinHilbe (textbook treatment); generalized linear model framework
TypCensored regression (limited dependent variable)Generalized linear model for count data
Původní zdrojTobin, J. (1958). Estimation of Relationships for Limited Dependent Variables. Econometrica, 26(1), 24-36. DOI ↗Hilbe, J. M. (2011). Negative Binomial Regression (2nd ed.). Cambridge University Press. DOI ↗
Další názvycensored regression, limited dependent variable model, Tobit Modeli (Sansürlü Regresyon)NB regression, NB2 regression, negatif binom regresyonu
Příbuzné44
ShrnutíThe Tobit model is a regression for outcomes that are censored at a threshold, estimating the relationship by maximum likelihood. Introduced by James Tobin in 1958, it addresses the pile-up of observations at a limit (typically zero) in data such as spending, wages, or duration.Negative 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.
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ScholarGatePorovnat metody: Tobit Model · Negative Binomial Regression. Získáno 2026-06-15 z https://scholargate.app/cs/compare