手法を比較

	分位点回帰	リッジ回帰
分野	計量経済学	機械学習
系統	Regression model	Machine learning
提唱年	1978	1970
提唱者	Koenker & Bassett	Hoerl, A.E. & Kennard, R.W.
種類	Conditional quantile regression	L2-regularized linear regression
原典	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.	Hoerl, A.E. & Kennard, R.W. (1970). Ridge Regression: Biased Estimation for Nonorthogonal Problems. Technometrics, 12(1), 55–67.
別名	conditional quantile regression, regression quantiles, Kantil Regresyon	Ridge Regresyonu, ridge regresyonu, L2-regularized regression, Tikhonov regularization
関連	5	4
概要	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.	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.