Hypothesis Testing in the Bayesian Framework

Bayesian Fuzzy Hypothesis Testing with Imprecise Prior Distribution

This paper considers the testing of fuzzy hypotheses on the basis of a Bayesian approach. For this, using a notion of prior distribution with interval or fuzzy-valued parameters, we extend a concept of posterior probability of a fuzzy hypothesis. Some of its properties are also put into investigation. The feasibility and effectiveness of the proposed methods are also cla...

Bayesian Hypothesis Testing 1 Running head: BAYESIAN HYPOTHESIS TESTING The Need for Bayesian Hypothesis Testing in Psychological Science

Bayesian hypothesis testing for proportions

Most clinical trials contain tests on proportions, usually they are answered by means of the Frequentist approach, nevertheless another valid option could be to solve them using a Bayesian approach. The Bayesian approach has the advantage that it is not restricted to only one alternative hypothesis. Moreover, the hypotheses to be tested do not necessarily overlap. In this paper we show a SAS® m...

Multisource Bayesian sequential hypothesis testing

On some probability space (Ω,F,P), let (X)t≥0, 1 ≤ i ≤ d be d independent Brownian motions with constant drifts μ(i), 1 ≤ i ≤ d, and (T (j) n , Z n )n≥1, 1 ≤ j ≤ m be m independent compound Poisson processes independent of the Brownian motions (X)t≥0, 1 ≤ i ≤ d. For every 1 ≤ j ≤ m, (T (j) n )n≥1 are the arrival times, and (Z n )n≥1 are the marks on some measurable space (E, E), with arrival ra...

Using Bayesian Inference in Classical Hypothesis Testing

When students obtain a statistically significant sample at a 5% level of significance, they may conclude they can be 95% confident that the alternate hypothesis is true. From a classical perspective, this conclusion is unwarranted. Two elements may inadvertently support this unwarranted conclusion: the traditional definitions of Type I error and alpha, and the silence about confidence. From a B...