Quantile regression estimation for distortion measurement error data

Jun Zhang, Jiefei Wang, Cuizhen Niu and Ming Sun

Communications in Statistics - Theory and Methods, 2018, vol. 47, issue 20, 5107-5126

Abstract: We study the quantile estimation methods for the distortion measurement error data when variables are unobserved and distorted with additive errors by some unknown functions of an observable confounding variable. After calibrating the error-prone variables, we propose the quantile regression estimation procedure and composite quantile estimation procedure. Asymptotic properties of the proposed estimators are established, and we also investigate the asymptotic relative efficiency compared with the least-squares estimator. Simulation studies are conducted to evaluate the performance of the proposed methods, and a real dataset is analyzed as an illustration.

Date: 2018
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DOI: 10.1080/03610926.2017.1386319

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