Probability density estimation for survival data with censoring indicators missing at random

Qihua Wang, Wei Liu, Chunling Liu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

9 Citations (Scopus)


In this paper, some nonparametric approaches of density function estimation are developed when censoring indicators are missing at random. A conditional mean score based estimator and a mean score estimator are suggested, respectively. The two estimators are proved to be asymptotically normal and uniformly strongly consistent. The bandwidth selection problem is also discussed. A simulation study is conducted to compare finite-sample behaviors of the proposed estimators.
Original languageEnglish
Pages (from-to)835-850
Number of pages16
JournalJournal of Multivariate Analysis
Issue number5
Publication statusPublished - 1 May 2009
Externally publishedYes


  • 62E20
  • 62G05
  • Asymptotic normality
  • Bandwidth selection
  • Mean-squared error
  • Missing at random
  • primary
  • secondary
  • Strong consistency

ASJC Scopus subject areas

  • Statistics, Probability and Uncertainty
  • Numerical Analysis
  • Statistics and Probability

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