Titlebook: Linear and Graphical Models; for the Multivariate H. H. Andersen,M. Højbjerre,P. S. Eriksen Book 1995 Springer-Verlag New York, Inc. 1995 A

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The Complex Wishart Distribution and the Complex ,-distribution,Wishart distribution. Khatri (1965.), Khatri (1965.) and Giri (1965) make use of Goodmans results in further statistical analysis. The complex .-distribution is used in Gupta (1971). In this book the distributions are used in multivariate linear complex normal models in connection with distributiona

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Multivariate Linear Complex Normal Models,erature. In our presentation we make extensive use of vector space considerations and matrix algebra. First we define complex MANOVA models and then maximum likelihood estimation of the parameters in the complex MANOVA model is considered. We determine the maximum likelihood estimators and their dis

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Complex Normal Graphical Models,mplex normal distribution w.r.t. simple undirected graphs into consideration. This is the first published presentation of these models. Graphical models for the multivariate real normal distribution, also called covariance selection models, have already been studied in the literature. The initial wo

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Multivariate Linear Complex Normal Models,likelihood ratio test concerning the mean and test of independence in complex MANOVA models are presented. In both tests we find the likelihood ratio test statistic and its distribution. It turns out that the test statistics both are complex .-distributed.

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