Bayes Factors for Independence and Symmetry in Freund's Bivariate Exponetial Model with Censored Data
Jang Jung Sik, Dal Ho, Sang Gil
Abstract
Jang Jung Sik, Dal Ho, Sang Gil
Abstract
In this paper we consider the Bayesian hypothese testing for independence and symmetry in Freund's bivariate exponential model with censored data In Bayesian testing problem we use the noninformative priors for parameters which are improper and are defined only up to arbitrary constants. And we use the recently proposed hypotheses testing criterion called the intrinsic Bayes factor. Also we derive the arithmetic and median intrinsic Bayes factors and use these results of analyze some data sets.
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In this paper we consider the Bayesian hypothese testing for independence and symmetry in Freund's bivariate exponential model with censored data In Bayesian testing problem we use the noninformative priors for parameters which are improper and are defined only up to arbitrary constants. And we use the recently proposed hypotheses testing criterion called the intrinsic Bayes factor. Also we derive the arithmetic and median intrinsic Bayes factors and use these results of analyze some data sets.
Key concepts: Bivariate analysis, Bayes factor, Bayes' theorem, Mathematics, Prior probability, Independence (probability theory), Bayesian probability, Statistics