Penalized weighted composite quantile estimators with missing covariates

Hu Yang and Huilan Liu ()

Statistical Papers, 2016, vol. 57, issue 1, 69-88

Abstract: In this paper, we propose the penalized weighted composite quantile regression estimation for linear model when the covariates are missing at random. Under some mild conditions, the asymptotic normality, oracle property and Horvitz–Thompson property of the proposed estimators are established. Simulation results and a real data analysis are provided to examine the performance of our methods. Copyright Springer-Verlag Berlin Heidelberg 2016

Keywords: Composite quantile regression; Missing completely at random; Missing at random; Oracle property; Horvitz–Thompson property (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s00362-014-0642-2

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