Nonparametric bayes estimation of the survival function from a record of failures and follow-ups

DOI10.1080/03610929008830445zbMath0736.62036OpenAlexW2013702599MaRDI QIDQ3978049

Ram C. Tiwari, J. N. Zalkikar

Publication date: 25 June 1992

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610929008830445

zbMATH Keywords

weak convergencesquared error losssurvival functionstrong consistencyrandom censoring modelgeneralized maximum likelihood estimatorDirichlet process priormixture of Dirichlet processesmean square consistencyempirical Bayes estimatornonparametric Bayes estimatorfollow-uplimiting Bayes estimatorobserved failure timespartially observable censored data

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Bayesian problems; characterization of Bayes procedures (62C10) Empirical decision procedures; empirical Bayes procedures (62C12) Reliability and life testing (62N05)

Related Items (1)

Sharp bounds on distribution functions and expectations of mixtures of ordered families of distributions

Cites Work

• Large sample behaviour of the product-limit estimator on the whole line
• Empirical Bayes estimation of a distribution function
• On the posterior distribution of a Dirichlet process given randomly right censored observations
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• Bayesian nonparametric estimation based on censored data
• Tailfree and neutral random probabilities and their posterior distributions
• A large sample study of the life table and product limit estimates under random censorship
• A Bayesian analysis of some nonparametric problems
• Bayes and empirical bayes estimation of survival function under progressive censoring
• On estimating population characteristics from record-breaking observations II. Nonparametric results
• An emprical bayes approach to two-sample problems with censored data
• Nonparametric Bayesian Estimation of Survival Curves from Incomplete Observations
• Expressing the Kaplan-Meier Estimator as a Function of Empirical Subsurvival Functions
• Nonparametric Estimation of Lifetime Distributions from a Record of Failures and Follow-ups

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