The problem of robust hypothesis testing is studied, where under the null and alternative hypotheses, data-generating distributions are assumed to be in some uncertainty sets, goal design a test that performs well worst-case over sets. In this paper, sets constructed data-driven manner using kernel method, i.e., they centered around empirical training samples from respectively; constrained via ...

introduction studying motility of biological objects is an important parameter in many biomedical processes. therefore, automated analyzing methods via microscopic videos are becoming an important step in recent researches. materials and methods in the proposed method of this article, a hypothesis testing function is defined to separate biological particles from artifact and noise in captured v...

introduction in recent years methods based on radio frequency waves have been used for detecting breast cancer. using theses waves leads to better results in early detection of breast cancer comparing with conventional mammography which has been used during several years. materials and methods in this paper, a new method is introduced for detection of backscattered signals which are received by...

Mardia et al. (1979, p. 121) reprint data from Frets (1921) giving the length and breadth (in millimeters) of the heads of the first and second son in a sample of n = 25 families, from a study of heredity in humans. If we assume a multivariate normal model then the following statistics are sufficient:

We have seen so far two types of statistical estimation frameworks: confidence intervals and point estimation. Hypothesis testing is a third inference framework that is concerned with choosing a hypothesis supported by available data out of a number of competing alternatives. We start with the basic definitions and then proceed to describe a few important cases. We assume that we have data X1, ...