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Analysis of multivariate repeated measures data using a MANOVA model and principal components

100%

Krzysko M., Smiałowski T., Wołynski W.

Biometrical Letters

2014

tom 51

nr 2

103-114

In this paper we consider a set of T repeated measurements on p characteristics on each of n individuals. The n individuals themselves may be divided and randomly assigned to K groups. These data are analyzed using a mixed effect MANOVA model, assuming that the data on an individual have a covariance matrix which is a Kronecker product of two positive definite matrices. Results are illustrated on a data set obtained from experiments with varieties of winter rye.

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Classifiers for doubly multivariate data

86%

Krzyśko M., Skorzybut M., Wołyński W.

Discussiones Mathematicae Probability and Statistics

2011

tom 31

nr 1-2

5-27

This paper proposes new classifiers under the assumption of multivariate normality for multivariate repeated measures data (doubly multivariate data) with Kronecker product covariance structures. These classifiers are especially useful when the number of observations is not large enough to estimate the covariance matrices, and thus the traditional classifiers fail. The quality of these new classifiers is examined on some real data. Computational schemes for maximum likelihood estimates of required class parameters, and the likelihood ratio test relating to the structure of the covariance matrices, are also given.

Ograniczanie wyników

1 Biometrical Letters

1 Discussiones Mathematicae Probability and Statistics

1 Krzysko M.

1 Krzyśko M.

1 Skorzybut M.

1 Smiałowski T.

1 Wołynski W.

1 Wołyński W.

1 2014

1 2011

Wyniki wyszukiwania

Analysis of multivariate repeated measures data using a MANOVA model and principal components

Classifiers for doubly multivariate data