DGQR estimation for interval censored quantile regression with varying-coefficient models
Open Access
- 10 November 2020
- journal article
- research article
- Published by Public Library of Science (PLoS) in PLOS ONE
- Vol. 15 (11), e0240046
- https://doi.org/10.1371/journal.pone.0240046
Abstract
This paper propose a direct generalization quantile regression estimation method (DGQR estimation) for quantile regression with varying-coefficient models with interval censored data, which is a direct generalization for complete observed data. The consistency and asymptotic normality properties of the estimators are obtained. The proposed method has the advantage that does not require the censoring vectors to be identically distributed. The effectiveness of the method is verified by some simulation studies and a real data example.Funding Information
- National Natural Science Foundation of China (11671054)
- National Natural Science Foundation of China (11901053)
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