Linear and Graphical Models : For the Multivariate Complex Normal Distribution downloadPDF, EPUB, MOBI
Linear and Graphical Models : For the Multivariate Complex Normal Distribution downloadPDF, EPUB, MOBI
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Author: Heidi H. Andersen
Number of Pages: 183 pages
Published Date: 19 May 1995
Publisher: Springer-Verlag New York Inc.
Publication Country: New York, NY, United States
Language: English
ISBN: 9780387945217
Download Link: Linear and Graphical Models For the Multivariate Complex Normal Distribution
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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.
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Linear and Graphical Models : For the Multivariate Complex Normal Distribution. Heidi H. Andersen
Author: Heidi H. Andersen
Number of Pages: 183 pages
Published Date: 19 May 1995
Publisher: Springer-Verlag New York Inc.
Publication Country: New York, NY, United States
Language: English
ISBN: 9780387945217
Download Link: Linear and Graphical Models For the Multivariate Complex Normal Distribution
---------------------------------------------------------------
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.
Read online Linear and Graphical Models : For the Multivariate Complex Normal Distribution Buy and read online Linear and Graphical Models : For the Multivariate Complex Normal Distribution Download Linear and Graphical Models : For the Multivariate Complex Normal Distribution ebook, pdf, djvu, epub, mobi, fb2, zip, rar, torrent Download to iPad/iPhone/iOS, B&N nook Linear and Graphical Models : For the Multivariate Complex Normal Distribution ebook, pdf, djvu, epub, mobi, fb2, zip, rar, torrent
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