Regression model
Quantile Regression
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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Sources
- Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI: 10.2307/1913643 ↗
- Koenker, R. (2005). Quantile Regression. Cambridge University Press. DOI: 10.1017/CBO9780511754098 ↗
Related methods
Referenced by
2SLS RegressionARFIMA ModelBayesian Quantile RegressionBayesian Quantile-on-Quantile RegressionBayesian Robust RegressionBeta RegressionBlock BootstrapBreakdown Point AnalysisConditional Value-at-RiskConformal Prediction (Time Series)Elastic Net RegressionFourier Quantile-on-Quantile RegressionGAMLSSGARCH ModelHeckman Selection ModelHeterogeneous Treatment Effect Fuzzy Regression DiscontinuityHeterogeneous Treatment Effect Regression Discontinuity DesignHeteroscedasticity-Robust Standard ErrorsHuber RegressionInfluence DiagnosticsKernel Density EstimationLeast Median of SquaresLeast Trimmed SquaresM-EstimatorMAD EstimationNARDL ModelNonlinear ARDLOLS RegressionOrdinal Logistic RegressionPoisson RegressionProbit ModelQuantile-on-Quantile RegressionRANSAC RegressionRobust ARCH modelRobust ARIMA modelRobust CorrelationRobust GARCH modelRobust Linear RegressionRobust Logistic RegressionRobust Multiple linear regressionRobust NARDLRobust OLSRobust Quantile RegressionRobust Quantile-on-Quantile RegressionRobust RegressionRobust Simple linear regressionRobust WLSS-EstimatorSn and Qn Scale EstimatorsSpatial RegressionSTAR ModelStochastic Frontier AnalysisStructural Break Quantile-on-Quantile RegressionTail Risk MeasuresTheil-Sen EstimatorThreshold RegressionTime-varying parameter quantile-on-quantile regressionTobit Model