A new minimal training sample scheme for intrinsic Bayes factors in censored data

DOI10.1016/J.CSDA.2014.07.012OpenAlexW2057803882MaRDI QIDQ1623725

Silvia Perra, Stefano Cabras, María Eugenia Castellanos

Publication date: 23 November 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2014.07.012

zbMATH Keywords

model selectionsurvival analysisKaplan-Meier estimatorintrinsic Bayes factorimproper priors

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Bayesian inference (62F15) Reliability and life testing (62N05)

Related Items (4)

Model Uncertainty Quantification in Cox Regression ⋮ Detecting renewal states in chains of variable length via intrinsic Bayes factors ⋮ A model selection approach for variable selection with censored data ⋮ Optimality of training/test size and resampling effectiveness in cross-validation

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