Comparer des méthodes

	RANSAC Regression	Régression quantile
Domaine	Statistique	Économétrie
Famille	Regression model	Regression model
Année d'origine	1981	1978
Auteur d'origine	Fischler & Bolles	Koenker & Bassett
Type	Robust linear regression	Conditional quantile regression
Source fondatrice	Fischler, M. A. & Bolles, R. C. (1981). Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography. Communications of the ACM, 24(6), 381-395.	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.
Alias	random sample consensus, RANSAC, robust regression, RANSAC Regresyonu	conditional quantile regression, regression quantiles, Kantil Regresyon
Apparentées	5	5
Résumé	RANSAC Regression is a robust linear regression method introduced by Fischler and Bolles in 1981 that fits a model to the inlier points of a dataset while automatically excluding outliers. Instead of fitting all the data at once, it repeatedly samples small subsets, fits a candidate model, and keeps the model that wins the largest consensus of agreeing points.	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.