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Probit regressionsmodell×Kvantilregression×
ÄmnesområdeEkonometriEkonometri
FamiljRegression modelRegression model
Ursprungsår20181978
UpphovspersonGreene (textbook treatment); classical discrete-choice modellingKoenker & Bassett
TypBinary discrete-choice modelConditional quantile regression
UrsprungskällaGreene, W. H. (2018). Econometric Analysis (8th ed.). Pearson. ISBN: 978-0134461366Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
Aliasprobit regression, normit model, Probit Modeliconditional quantile regression, regression quantiles, Kantil Regresyon
Närliggande55
SammanfattningThe probit model is a regression method for a binary (0/1) outcome that maps a linear index of the predictors through the standard normal cumulative distribution function to produce a probability. It is a classical discrete-choice alternative to logistic regression, developed in standard econometrics treatments such as Greene's Econometric Analysis (2018).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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ScholarGateJämför metoder: Probit Model · Quantile Regression. Hämtad 2026-06-15 från https://scholargate.app/sv/compare