Non parametric multivariate distribution estimation under right censoring

A non parametric estimator of the joint distribution function of a positive bivariate random vector is introduced. The case where one of the two variables is subject to right censoring is considered. To construct the proposed estimator, Poisson distributions are used for smoothing the empirical esti...

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Bibliographic Details
Published inCommunications in statistics. Theory and methods Vol. 53; no. 19; pp. 6785 - 6798
Main Authors Nafii, Adil, Bouezmarni, Taoufik, Mesfioui, Mhamed
Format Journal Article
LanguageEnglish
Published Philadelphia Taylor & Francis 01.10.2024
Taylor & Francis Ltd
Subjects
Asymptotic properties
Bivariate analysis
Distribution functions
joint distribution function
Normality
Poisson distribution
Poisson distributions
Random variables
right censoring
smooth non parametric estimation
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Summary:A non parametric estimator of the joint distribution function of a positive bivariate random vector is introduced. The case where one of the two variables is subject to right censoring is considered. To construct the proposed estimator, Poisson distributions are used for smoothing the empirical estimator of Stute ( 1993 ). The strong uniform convergence is established. Also, by stating the asymptotic i.i.d. representation, the asymptotic bias, variance, and normality are deduced. The smooth estimator is applied for analyzing survival data from patients with advanced lung cancer.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:0361-0926
1532-415X
DOI:10.1080/03610926.2023.2251624