Consider testing the composite hypothesis that a population is a particular discrete exponential family. For example, a Poisson distribution with unknown parameter. We find a sufficient condition for the admissibility of goodness of fit tests. Included in the class of admissible tests is the...

The problem is to estimate the mean of the selected population. The selection rule is to choose the population with the largest sample mean when such sample means are calculated from the first stage sample. An estimator of the selected mean is unbiased if its expected value equals the expected...

Let Ui = (Xi, Yi), i = 1, 2,..., n, be a random sample from a bivariate normal distribution with mean [mu] = ([mu]x, [mu]y) and covariance matrix . Let Xi, i = n + 1,..., N represent additional independent observations on the X population. Consider the hypothesis testing problem H0 : [mu] = 0...

Consider an r - c contingency table under the full multinomial model where each category is ordered. The problem is to test the null hypothesis of independence against the alternative that all local log odds ratios are nonnegative with a least one local log odds ratio positive. We find the class...

Under the model of independent test statistics, we propose a two-parameter family of Bayes multiple testing procedures. The two parameters can be viewed as tuning parameters. Using the Benjamini--Hochberg step-up procedure for controlling false discovery rate as a baseline for conservativeness,...

The change point problem for independent normal means is considered as a multiple testing problem. Two stepwise methods are considered. Namely, the binary segmentation method of Vostrikova (1981) [7] and the maximum residual down method of Cohen et al. (2009) [5]. Both of these methods are shown...

Consider k-independent normal populations with unknown means. Test the null hypothesis that the vector of means lies in a linear subspace (For example, the null could be all parameters are equal.) The alternative is that the vector of means lies in a closed convex cone (but not a linear...

Similarity of a test is often a necessary condition for a test to be unbiased (in particular for a test to be uniformly most powerful unbiased when such a test exists). Lehmann (Testing Statistical Hypotheses, 2nd Edition, Wiley, New York, 1986) describes the connection between similar tests and...