Comparer des méthodes

	Régression spatiale (modèles de retard spatial et d'erreur spatiale)	Régression quantile
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1988	1978
Auteur d'origine	Luc Anselin	Koenker & Bassett
Type	Spatial regression (cross-sectional)	Conditional quantile regression
Source fondatrice	Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic Publishers.	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.
Alias	spatial econometrics, spatial lag model, spatial error model, SAR / SEM	conditional quantile regression, regression quantiles, Kantil Regresyon
Apparentées	5	5
Résumé	Spatial regression is a family of regression models that build geographic neighbourhood relationships directly into the model, introduced by Luc Anselin in his 1988 treatment of spatial econometrics. It splits into a spatial lag model, where spatial dependence sits in the dependent variable, and a spatial error model, where the dependence sits in the error term.	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.