This paper deals with correlation tests from the class of spherical tests introduced by Läuter (Biometrics 52 (1996) 964). These methods provide an alternative to classical MANOVA approaches and are particularly useful in small samples. Following a brief introduction of the spherical tests, it...

Likelihood ratio tests for detecting a single outlier in multivariate linear models are considered, where an observation is called an outlier if there has been a shift in the mean. The test statistics are the maximum of n nonindependent statistics, where n is the number of observations. Relevant...

A new approach of estimating parameters in multivariate models is introduced. A fitting function will be used. The idea is to estimate parameters so that the fitting function equals or will be close to its expected value. The function will be decomposed into two parts. From one part, which will...

A unified approach of treating multivariate linear normal models is presented. The results of the paper are based on a useful extension of the growth curve model. In particular, the finding of maximum likelihood estimators when linear restrictions exist on the parameters describing the mean in...

This paper is concerned with an extended growth curve model with two within-individual design matrices which are hierarchically related. For the model some random-coefficient covariance structures are reduced. LR tests for testing the adequacy of each of these random-coefficient structures and...