DGQR estimation for interval censored quantile regression with varying-coefficient models

ChunJing Li, Yun Li, Xue Ding and XiaoGang Dong

PLOS ONE, 2020, vol. 15, issue 11, 1-17

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.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0240046

DOI: 10.1371/journal.pone.0240046

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