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क्वांटाइल रिग्रेशन×मजबूत सामान्यीकृत न्यूनतम वर्ग (मजबूत GLS)×
क्षेत्रअर्थमितिअर्थमिति
परिवारRegression modelRegression model
उद्भव वर्ष19781936 / 1980
प्रवर्तकKoenker & BassettAitken (GLS theory, 1936); White (robust covariance, 1980)
प्रकारConditional quantile regressionRobust linear regression
मौलिक स्रोतKoenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗Greene, W. H. (2012). Econometric Analysis (7th ed.). Pearson. Chapter 9: The Generalized Regression Model and Heteroscedasticity. ISBN: 978-0131395381
उपनामconditional quantile regression, regression quantiles, Kantil Regresyonrobust generalized least squares, GLS with robust standard errors, heteroscedasticity-consistent GLS, HC-GLS
संबंधित55
सारांशQuantile 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.Robust GLS extends classical Generalized Least Squares by pairing GLS coefficient estimation with heteroscedasticity- and autocorrelation-consistent (HAC) standard errors, or by using M-estimation within the GLS framework. It corrects for non-spherical errors — heteroscedasticity, autocorrelation, or both — while also guarding inference against misspecification of the error covariance structure.
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ScholarGateविधियों की तुलना करें: Quantile Regression · Robust GLS. 2026-06-18 को यहाँ से प्राप्त https://scholargate.app/hi/compare