Estimation and test procedures for composite quantile regression with covariates missing at random
In this paper, we study the weighted composite quantile regression (WCQR) for general linear model with missing covariates. We propose the WCQR estimation and bootstrap test procedures for unknown parameters. Simulation studies and a real data analysis are conducted to examine the finite performance of our proposed methods.
Year of publication: |
2014
|
---|---|
Authors: | Ning, Zijun ; Tang, Linjun |
Published in: |
Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 95.2014, C, p. 15-25
|
Publisher: |
Elsevier |
Subject: | Composite quantile regression | General linear model | Missing covariates | Bootstrap |
Saved in:
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