Linear and Graphical Models: for the Multivariate Complex Normal Distribution: 101 (Lecture Notes in Statistics, 101) - Softcover
Book 8 of 72: Lecture Notes in Statistics
Synopsis
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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Synopsis
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 (Lecture Notes in Statistics, 101)
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Springer (edition Softcover reprint of the original 1st ed. 1995), 1995
ISBN 10: 0387945210
ISBN 13: 9780387945217
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Linear and Graphical Models: For the Multivariate Complex Normal Distribution (Softcover Reprint of the Original 1st 1995)
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Linear and Graphical Models: for the Multivariate Complex Normal Distribution (Lecture Notes in Statistics, 101)
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Linear and Graphical Models: for the Multivariate Complex Normal Distribution (Lecture Notes in Statistics, 101)
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Linear and Graphical Models: for the Multivariate Complex Normal Distribution (Lecture Notes in Statistics, 101)
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Linear and Graphical Models
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 200 pp. Englisch. Seller Inventory # 9780387945217
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 multivaria. Seller Inventory # 5912059
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Linear and Graphical Models: for the Multivariate Complex Normal Distribution
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Linear and Graphical Models : for the Multivariate Complex Normal Distribution
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Condition: Gut. Zustand: Gut | Sprache: Englisch | Produktart: Bücher | 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. Seller Inventory # 1537775/203
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Linear and Graphical Models | for the Multivariate Complex Normal Distribution
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Taschenbuch. Condition: Neu. Linear and Graphical Models | for the Multivariate Complex Normal Distribution | Heidi H. Andersen (u. a.) | Taschenbuch | 183 S. | Englisch | 1995 | Springer | EAN 9780387945217 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Seller Inventory # 101733934