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Linear and Graphical Models: for the Multivariate Complex Normal Distribution - Malene Hojbjerre,Heidi H. Andersen,Poul S. Eriksen,Dorte Sorensen

Anglų
1995-05-19
120,11 € 184,78 €

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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 comple ... Visas aprašymas

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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.

Daugiau informacijos

Autorius Malene Hojbjerre, Heidi H. Andersen, Poul S. Eriksen, Dorte Sorensen
Leidėjas Springer US
Series Lecture Notes in Statistics
Išleidimo metai 1995
Viršelio tipas Minkšti viršeliai
EAN 9780387945217
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120,11 € 184,78 €