THE MOST STRINGENT SOMEWHERE MOST POWERFUL ONE SIDED TEST OF THE MULTIVARIATE NORMAL MEAN

Locally Most Powerful Sequential Tests of a Simple Hypothesis vs One-Sided Alternatives

Let X1,X2, . . . be a discrete-time stochastic process with a distribution Pθ, θ ∈ Θ, where Θ is an open subset of the real line. We consider the problem of testing a simple hypothesis H0 : θ = θ0 versus a composite alternative H1 : θ > θ0, where θ0 ∈ Θ is some fixed point. The main goal of this article is to characterize the structure of locally most powerful sequential tests in this problem. ...

The behavior of locally most powerful tests

The locally most powerful (LMP) tests of the hypothesis H : 6 = 6Q against one-sided as well as two-sided alternatives are compared with several competitive tests, as the likelihood ratio tests, the Wald-type tests and the Rao score tests, for several distribution shapes and for location, shape and vector parameters. A simulation study confirms the importance of the condition of local unbiasedn...

Estimation of the Multivariate Normal Mean under the Extended Reflected Normal Loss Function

Comparison between Frequentist Test and Bayesian Test to Variance Normal in the Presence of Nuisance Parameter: One-sided and Two-sided Hypothesis

 This article is concerned with the comparison P-value and Bayesian measure for the variance of Normal distribution with mean as nuisance paramete. Firstly, the P-value of null hypothesis is compared with the posterior probability when we used a fixed prior distribution and the sample size increases. In second stage the P-value is compared with the lower bound of posterior probability when the ...

Uniformly Most Powerful Bayesian Tests.

Uniformly most powerful tests are statistical hypothesis tests that provide the greatest power against a fixed null hypothesis among all tests of a given size. In this article, the notion of uniformly most powerful tests is extended to the Bayesian setting by defining uniformly most powerful Bayesian tests to be tests that maximize the probability that the Bayes factor, in favor of the alternat...