A General Framework for Robust Testing and Confidence Regions in High-Dimensional Quantile Regression

30 Dec 2014 Tianqi Zhao Mladen Kolar Han Liu

We propose a robust inferential procedure for assessing uncertainties of parameter estimation in high-dimensional linear models, where the dimension $p$ can grow exponentially fast with the sample size $n$. Our method combines the de-biasing technique with the composite quantile function to construct an estimator that is asymptotically normal... (read more)

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