A Simple Sequential Procedure for Testing Statistical Hypotheses

Sequential Testing of Simple Hypotheses about Compound Poisson Processes

One of two simple hypotheses is correct about the unknown arrival rate and jump distribution of a compound Poisson process. We start observing the process, and the problem is to decide on the correct hypothesis as soon as possible and with the smallest probability of wrong decision. We find a Bayes-optimal sequential decision rule and describe completely how to calculate its parameters without ...

TESTING STATISTICAL HYPOTHESES UNDER FUZZY DATA AND BASED ON A NEW SIGNED DISTANCE

This paper deals with the problem of testing statisticalhypotheses when the available data are fuzzy. In this approach, wefirst obtain a fuzzy test statistic based on fuzzy data, and then,based on a new signed distance between fuzzy numbers, we introducea new decision rule to accept/reject the hypothesis of interest.The proposed approach is investigated for two cases: the casewithout nuisance p...

Testing Simple Hypotheses

We introduce a neutral statistic S that makes the Conditional Frequentist error reports identical to Bayesian posterior probabilities of the hypotheses. In symmetrical cases we can show this strategy to be optimal from the Frequentist perspective. A Conditional Frequentist who uses such a strategy can exploit the consistency of the method with the Likelihood Principle—for example, the validity ...

Statistical Testing of Hypotheses

GroupTest: Multiple Testing Procedure for Grouped Hypotheses

In the modern Big Data analysis, testing multiple hypotheses simultaneously has been an important tool in analyzing data arising from scientific studies, such as genetics, astronomy, social sciences and many others. The hypotheses can often be grouped together according to the nature of the scientific investigations. For instance, genes can be grouped according to gene pathways; the nearby pixe...