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Robust Quantile Regression

Robust Quantile Regression estimates conditional quantiles of a response variable while simultaneously downweighting the influence of outliers. By combining the asymmetric loss function of standard quantile regression with bounded-influence or M-estimation weights, it provides reliable quantile estimates even when data contain extreme observations or heavy-tailed error distributions.

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Taksonoomiline meetodikirje · regression-model / statistics

Koenker, R. (2005). Quantile Regression. Cambridge University Press. · ISBN 978-0521608275
Machado, J. A. F. (1993). Robust model selection and M-estimation. Econometric Theory, 9(3), 478–493. · DOI 10.1017/S0266466600007775

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