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On nonparametric maximum likelihood estimation with interval censoring and left truncation
Author(s) -
Hudgens Michael G.
Publication year - 2005
Publication title -
journal of the royal statistical society: series b (statistical methodology)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.523
H-Index - 137
eISSN - 1467-9868
pISSN - 1369-7412
DOI - 10.1111/j.1467-9868.2005.00516.x
Subject(s) - censoring (clinical trials) , mathematics , nonparametric statistics , estimator , statistics , maximum likelihood , truncation (statistics) , likelihood function , maximum likelihood sequence estimation
Summary. A graph theoretical approach is employed to describe the support set of the nonparametric maximum likelihood estimator for the cumulative distribution function given interval‐censored and left‐truncated data. A necessary and sufficient condition for the existence of a nonparametric maximum likelihood estimator is then derived. Two previously analysed data sets are revisited.