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What is quantile regression?

Updated: 4/28/2022
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∙ 15y ago

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Quantile regression is considered a natural extension of ordinary least squares. Instead of estimating the mean of the regressand for a given set of regressors, and instead of minimizing sum of squares, it estimates different values of the regressand across its distribution, and minimizes instead the absolute distances between observations.

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Victor Chernozhukov has written: 'Quantile regression with censoring and endogeneity' 'An IV model of quantile treatment effects' -- subject(s): Accessible book 'Rearranging Edgeworth-Cornish-Fisher expansions' 'L1-Penalized Quantile Regression in High Dimensional Sparse Models' -- subject(s): Regression analysis 'Instrumental variable quantile regression' -- subject(s): Accessible book 'Extremal quantities and value-at-risk' -- subject(s): Accessible book 'Estimation and confidence regions for parameter sets in econometric models' -- subject(s): Accessible book


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