Third-order power comparisons for a class of tests for multivariate linear hypothesis under general distributions

Pragmatic, Unifying Algorithm Gives Power Probabilities for Common F Tests of the Multivariate General Linear Hypothesis

We consider the problem of computing the power of some usual F transforms of the Wilks U, Hotelling-Lawley T, and Pillai V statistics for testing H0: CBA = Œ0 under the multivariate general linear model, Y = XB + ‰ , where the rows of ‰A are taken as independent N(0, Í) random vectors. Keeping all these matrices at full rank, let C be rC × rX and A be P × rA. For determining p-values, Fi (i ∈ {...

I . I I A CLASS OF RANK - ORDER TESTS FOR A GENERAL LINEAR HYPOTHESIS by Madan Lal Puri

A Class of Tests for Multivariate Normality Based on Linear Functions of Order Statistics

Asymptotic expansions of the null distributions of test statistics for multivariate linear hypothesis under nonnormality

This paper is concerned with the distributions of some test statistics for a multivariate linear hypothesis under nonnormality. The test statistics considered include the likelihood ratio statistic, the Lawley-Hotelling trace criterion and the BartlettNanda-Pillai trace criterion, under normality. We derive asymptotic expansions of the null distributions of these test statistics up to the order...

Hypothesis Tests for Multivariate Linear Models Using the car Package

The multivariate linear model is Y (n×m) = X (n×p) B (p×m) + E (n×m) The multivariate linear model can be fit with the lm function in R, where the left-hand side of the model comprises a matrix of response variables, and the right-hand side is specified exactly as for a univariate linear model (i.e., with a single response variable). This paper explains how to use the Anova and linearHypothesis...