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Kvantilna regresija×Rigidna regresija×
OblastEkonometrijaMašinsko učenje
PorodicaRegression modelMachine learning
Godina nastanka19781970
TvoracKoenker & BassettHoerl, A.E. & Kennard, R.W.
TipConditional quantile regressionL2-regularized linear regression
Temeljni izvorKoenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗Hoerl, A.E. & Kennard, R.W. (1970). Ridge Regression: Biased Estimation for Nonorthogonal Problems. Technometrics, 12(1), 55–67. DOI ↗
Drugi naziviconditional quantile regression, regression quantiles, Kantil RegresyonRidge Regresyonu, ridge regresyonu, L2-regularized regression, Tikhonov regularization
Srodne54
SažetakQuantile 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.Ridge Regression is an L2-regularized linear regression method, introduced by Arthur Hoerl and Robert Kennard in 1970, that reduces multicollinearity by adding a penalty on the size of the coefficients. It shrinks coefficients toward zero without setting any of them exactly to zero, producing more stable estimates when predictors are highly correlated.
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ScholarGateUporedite metode: Quantile Regression · Ridge Regression. Preuzeto 2026-06-17 sa https://scholargate.app/sr/compare