Nonparametric quantile regression estimation for functional data with responses missing at random

Dengke Xu and Jiang Du ()
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Dengke Xu: Zhejiang Agriculture and Forestry University
Jiang Du: Beijing University of Technology

Metrika: International Journal for Theoretical and Applied Statistics, 2020, vol. 83, issue 8, No 6, 977-990

Abstract: Abstract This paper presents the nonparametric quantile regression estimation for the regression function operator when the functional data with the responses missing at random are considered. Then, the large sample properties of the proposed estimator are established under some mild conditions. Finally, a simulation study is conducted to investigate the finite sample properties of the proposed method.

Keywords: Quantile regression; Functional data analysis; Missing at random; Inverse probability weighting estimator; Asymptotic normality; 62G08; 62G20 (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s00184-020-00769-z

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