Based on Läuter's [Läuter, J., 1996. Exact t and F tests for analyzing studies with multiple endpoints. Biometrics 52, 964-970] exact t test for biometrical studies related to the multivariate normal mean, we develop a generalized F-test for the multivariate normal mean and extend it to multiple comparison. The proposed generalized F-tests have simple approximate null distributions. A Monte Carlo study and two real examples show that the generalized F-test is at least as good as the optional individual Läuter's test and can improve its performance in some situations where the projection directions for the Läuter's test may not be suitably chosen. The generalized F-test could be superior to individual Läuter's tests and the classical Hotelli...
AbstractA method of testing the hypothesis of the kind H0:C′Φ1M=C′Φ2M in two independent multivariat...
A class of tests for normality using the ratio of two estimates of the standard deviation is general...
To test for equality of variances given two independent random samples from univariate normal popula...
Based on Lauter\u27s (Biometrics, 1996) exact t test for biometrical studies related to the multivar...
In this thesis we introduce, implement and compare several multivariate goodness-of-fit tests. First...
In this article, we propose a new multiple test procedure for assessing multivariate normality, whic...
We study the empirical size and power of some recently proposed tests for multivariate normality (MV...
This book focuses on all-pairwise multiple comparisons of means in multi-sample models, introducing ...
A Monte Carlo power study of 10 multivariate normality goodness-of-fit tests is presented. First, mu...
Multivariate statistical methods often require the assumption of multivariate normality. The purpose...
The methodology developed in Somerville (Proceedings of the 25th Symposium on the Interface, Computi...
A multiple test procedure for assessing multivariate normality (MVN) is proposed. The new test combi...
AbstractA Monte Carlo power study of 10 multivariate normality goodness-of-fit tests is presented. F...
We propose a test for multisample comparison studies that can be applied without strict assumptions,...
The classic F test for the hypothesis concerning the equality of two population variances is known ...
AbstractA method of testing the hypothesis of the kind H0:C′Φ1M=C′Φ2M in two independent multivariat...
A class of tests for normality using the ratio of two estimates of the standard deviation is general...
To test for equality of variances given two independent random samples from univariate normal popula...
Based on Lauter\u27s (Biometrics, 1996) exact t test for biometrical studies related to the multivar...
In this thesis we introduce, implement and compare several multivariate goodness-of-fit tests. First...
In this article, we propose a new multiple test procedure for assessing multivariate normality, whic...
We study the empirical size and power of some recently proposed tests for multivariate normality (MV...
This book focuses on all-pairwise multiple comparisons of means in multi-sample models, introducing ...
A Monte Carlo power study of 10 multivariate normality goodness-of-fit tests is presented. First, mu...
Multivariate statistical methods often require the assumption of multivariate normality. The purpose...
The methodology developed in Somerville (Proceedings of the 25th Symposium on the Interface, Computi...
A multiple test procedure for assessing multivariate normality (MVN) is proposed. The new test combi...
AbstractA Monte Carlo power study of 10 multivariate normality goodness-of-fit tests is presented. F...
We propose a test for multisample comparison studies that can be applied without strict assumptions,...
The classic F test for the hypothesis concerning the equality of two population variances is known ...
AbstractA method of testing the hypothesis of the kind H0:C′Φ1M=C′Φ2M in two independent multivariat...
A class of tests for normality using the ratio of two estimates of the standard deviation is general...
To test for equality of variances given two independent random samples from univariate normal popula...