Reliable survival analysis based on the Dirichlet process

DOI10.1002/BIMJ.201500062zbMath1386.62057OpenAlexW2133167407WikidataQ40618974 ScholiaQ40618974MaRDI QIDQ154684

Cassio P. De Campos, Francesca Mangili, Alessio Benavoli, Marco Zaffalon, Alessio Benavoli, Cassio Polpo de Campos, Marco Zaffalon, Francesca Mangili

Publication date: 22 August 2015

Published in: Biometrical Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/bimj.201500062

zbMATH Keywords

survival analysisBayesian nonparametricsDirichlet processcensored datalog-rank testprior near-ignorance

Mathematics Subject Classification ID

Density estimation (62G07) Applications of statistics to biology and medical sciences; meta analysis (62P10) Reliability and life testing (62N05)

Related Items (3)

IDPSurvival ⋮ A robust algorithm for explaining unreliable machine learning survival models using the Kolmogorov-Smirnov bounds ⋮ Unnamed Item

Uses Software

• R
• survival

Cites Work

• Unnamed Item
• Unnamed Item
• Nonparametric Bayes estimators based on beta processes in models for life history data
• A note on the uniform consistency of the Kaplan-Meier estimator
• On the posterior distribution of a Dirichlet process given randomly right censored observations
• Bayesian nonparametric estimation based on censored data
• An overview of robust Bayesian analysis. (With discussion)
• Survival analysis. Techniques for censored and truncated data.
• A Bayesian analysis of some nonparametric problems
• Nonparametric Estimation from Incomplete Observations
• The Influence Curve and Its Role in Robust Estimation
• Nonparametric Bayesian Estimation of Survival Curves from Incomplete Observations
• Bayesian Robustness
• On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other

This page was built for publication: Reliable survival analysis based on the Dirichlet process