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A Generalization of Turnbull’s Estimator for Interval-Censored and Doubly Truncated Data

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  • Pao-Sheng Shen

Abstract

Nonparametric estimates of the conditional distribution of a response variable given a covariate are important for data exploration purposes. In this article, we propose a nonparametric estimator of the conditional distribution function in the case where the response variable is subject to interval censoring and double truncation. Using the approach of Dehghan and Duchesne (2011), the proposed method consists in adding weights that depend on the covariate value in the self-consistency equation of Turnbull (1976), which results in a nonparametric estimator. We demonstrate by simulation that the estimator, bootstrap variance estimation and bandwidth selection all perform well in finite samples.

Suggested Citation

  • Pao-Sheng Shen, 2014. "A Generalization of Turnbull’s Estimator for Interval-Censored and Doubly Truncated Data," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 43(14), pages 2958-2972, July.
    • Handle: RePEc:taf:lstaxx:v:43:y:2014:i:14:p:2958-2972
    DOI: 10.1080/03610926.2012.689065
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