Locally best rotation-invariant rank tests for modal location

Skewness and kurtosis as locally best invariant tests of normality

Consider testing normality against a one-parameter family of univariate distributions containing the normal distribution as the boundary, e.g., the family of t-distributions or an infinitely divisible family with finite variance. We prove that under mild regularity conditions, the sample skewness is the locally best invariant (LBI) test of normality against a wide class of asymmetric families a...

I Sequential Rank Tests for Location

MATHEMATICAL ENGINEERING TECHNICAL REPORTS Skewness and kurtosis as locally best invariant tests of normality

Consider testing normality against a one-parameter family of univariate distributions containing the normal distribution as the boundary, e.g., the family of t-distributions or an infinitely divisible family with finite variance. We prove that under mild regularity conditions, the sample skewness is the locally best invariant (LBI) test of normality against a wide class of asymmetric families a...

Some Locally Most Powerful Rank Tests For Correlation

Affine Invariant Multivariate Rank Tests for Several Samples

Affine invariant analogues of the two-sample Mann-Whitney-Wilcoxon rank sum test and the c-sample Kruskal-Wallis test for the multivariate location model are introduced. The definition of a multivariate (centered) rank function in the development is based on the Oja criterion function. This work extends bivariate rank methods discussed by Brown and Hettmansperger (1987a,b) and multivariate sign...