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Linear and Graphical Models: for the Multivariate Complex Normal Distribution (Lecture Notes in Statistics, 101) by Heidi H. Andersen, Malene Hojbjerre, Dorte Sorensen, Poul S. Eriksen is a nonfiction available to read on EtoBox.

What is Linear and Graphical Models: for the Multivariate Complex Normal Distribution (Lecture Notes in Statistics, 101) about?

In The Last Decade, Graphical Models Have Become Increasingly Popular As A Statistical Tool. This Book Is The First Which Provides An Account Of Graphical Models For Multivariate Complex Normal Distributions. Beginning With An Introduction To The Multivariate Complex Normal Distribution, The Authors Develop The Marginal And Conditional Distributions Of Random Vectors And Matrices. Then They Introduce Complex Manova Models And Parameter Estimation And Hypothesis Testing For These Models. After Introducing Undirected Graphs, They Then Develop The Theory Of Complex Normal Graphical Models Including The Maximum Likelihood Estimation Of The Concentration Matrix And Hypothesis Testing Of Conditional Independence. H.h. Andersen ... [et Al.]. Includes Bibliographical References (p. - ) And Index.

Who reads Linear and Graphical Models: for the Multivariate Complex Normal Distribution (Lecture Notes in Statistics, 101)?

Author

Heidi H. Andersen, Malene Hojbjerre, Dorte Sorensen, Poul S. Eriksen

Publisher

Springer-Verlag

Published

1995

Language

EN

ISBN

9781461242406

Category

nonfiction

Subjects

Mathematics, Stem