Estimation and inferences for varying coefficient partially nonlinear quantile models with censoring indicators missing at random

Xiaoshuang Zhou () and Peixin Zhao
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Xiaoshuang Zhou: Dezhou University
Peixin Zhao: Chongqing Technology and Business University

Computational Statistics, 2022, vol. 37, issue 4, No 7, 1727-1750

Abstract: Abstract In this paper, we focus on the varying coefficient partially nonlinear quantile regression model when the response variable is right censored and the censoring indicator is missing at random. Based on the calibration and imputation estimation methods, the three-stage approaches are carried out to construct the estimators of the parameter vector in the nonlinear function part and the nonparametric varying-coefficient functions involved in the model. Under some appropriate conditions, the asymptotic properties of the proposed estimators are established. Simulation study and a real data analysis are performed to illustrate the performances of our proposed estimators.

Keywords: Varying coefficient partially nonlinear model; Quantile regression; Censoring data; Missing at random (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s00180-021-01192-2

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