Algorithms for computing self-consistent and maximum likelihood estimators with doubly censored data

DOI10.1214/aos/1032298293zbMath0867.62019OpenAlexW2095895968MaRDI QIDQ1354409

Jian-Jian Ren, Per Aslak Mykland

Publication date: 3 August 1997

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1214/aos/1032298293

zbMATH Keywords

algorithmsEM algorithmsurvival functionnonparametric maximum likelihood estimatordoubly censored datafixed point problemself-consistent estimators

Mathematics Subject Classification ID

Nonparametric estimation (62G05) Order statistics; empirical distribution functions (62G30) Probabilistic methods, stochastic differential equations (65C99)

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Cites Work

• Unnamed Item
• Asymptotic properties of self-consistent estimators based on doubly censored data
• Weak convergence of a self-consistent estimator of the survival function with doubly censored data
• On the convergence properties of the EM algorithm
• A large sample study of generalized maximum likelihood estimators from incomplete data via self-consistency
• Strong consistency of a nonparametric estimator of the survival function with doubly censored data
• Generalized Cramér-von Mises tests of goodness of fit for doubly censored data
• Nonparametric Estimation of a Survivorship Function with Doubly Censored Data
• A generalized two-sample Wilcoxon test for doubly censored data
• A Decomposable Nonlinear Programming Approach
• The Power of the Likelihood Ratio Test

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