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Elastic-Net-Regression×Quantile Regression×
FachgebietStatistikÖkonometrie
FamilieRegression modelRegression model
Entstehungsjahr20051978
UrheberHui Zou and Trevor HastieKoenker & Bassett
TypPenalized linear regressionConditional quantile regression
Wegweisende QuelleZou, H., & Hastie, T. (2005). Regularization and variable selection via the elastic net. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 67(2), 301-320. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
Aliasnamenelastic net, EN regression, L1+L2 regularized regression, combined lasso-ridge regressionconditional quantile regression, regression quantiles, Kantil Regresyon
Verwandt65
ZusammenfassungElastic net regression combines the L1 (lasso) and L2 (ridge) penalties into a single regularized regression framework. Controlled by a mixing parameter alpha and a shrinkage strength lambda, it can simultaneously select variables and handle correlated predictors — overcoming key limitations of pure lasso and pure ridge applied alone.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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ScholarGateMethoden vergleichen: Elastic Net Regression · Quantile Regression. Abgerufen am 2026-06-17 von https://scholargate.app/de/compare