Survey Methodology
Weighted censored quantile regression
by Chithran Vasudevan, Asokan Mulayath Variyath and Zhaozhi FanNote 1
- Release date: May 7, 2019
Abstract
In this paper, we make use of auxiliary information to improve the efficiency of the estimates of the censored quantile regression parameters. Utilizing the information available from previous studies, we computed empirical likelihood probabilities as weights and proposed weighted censored quantile regression. Theoretical properties of the proposed method are derived. Our simulation studies shown that our proposed method has advantages compared to standard censored quantile regression.
Key Words: Empirical Likelihood; Right censoring; Kaplan-Meier Estimator.
Table of contents
- Section 1. Introduction
- Section 2. Estimation of weights using empirical likelihood
- Section 3. Estimation of weighted censored quantile regression parameters
- Section 4. Performance analysis
- Section 5. Conclusions
- Acknowledgements
- References
How to cite
Vasudevan, C., Variyath, A.M. and Fan, Z. (2019). Weighted censored quantile regression. Survey Methodology, Statistics Canada, Catalogue No. 12-001-X, Vol. 45, No. 1. Paper available at https://www150.statcan.gc.ca/n1/pub/12-001-x/2019001/article/00004-eng.htm.
Note
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