Bayesian significance test for discriminating between survival distributions. Issue 24 (17th December 2018)

• Record Type: Journal Article
• Authors: Assane, Cachimo Combo; Pereira, Basilio de Bragança; Pereira, Carlos Alberto de Bragança
• Is Part Of: Communications in statistics. Volume 47:Issue 24(2018)
• Page Start: 6095
• Page End: 6107
• Publication Date: 2018-12-17
• Subjects: FBST -- Mixture model -- Model choice -- Separate models -- Significance test -- Survival distributions.; 62F15 -- 62F03; Mathematical statistics -- Periodicals; Mathematics; Statistics; 519.2
• DOI: 10.1080/03610926.2017.1406117
• Languages: English
• ISSNs: 0361-0926

Abstract

ABSTRACT: An evaluation of FBST, Fully Bayesian Significance Test, restricted to survival models is the main objective of the present paper. A Survival distribution should be chosen among the tree celebrated ones, lognormal, gamma, and Weibull. For this discrimination, a linear mixture of the three distributions is an important tool: the FBST is used to test the hypotheses defined on the mixture weights space. Another feature of the paper is that all three distributions are reparametrized in that all the six parameters are written as functions of the mean and the variance of the population been studied. Some numerical results from simulations with some right-censored data are considered.