Linear and Graphical Models - for the Multivariate Complex Normal Distribution (Paperback, Softcover reprint of the original 1st ed. 1995)

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.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Series:	Lecture Notes in Statistics, 101
Release date:	May 1995
First published:	1995
Authors:	Heidi H. Andersen • Malene Hojbjerre • Dorte Sorensen • Poul S. Eriksen
Dimensions:	235 x 155 x 14mm (L x W x T)
Format:	Paperback
Pages:	183
Edition:	Softcover reprint of the original 1st ed. 1995
ISBN-13:	978-0-387-94521-7
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics
LSN:	0-387-94521-0
Barcode:	9780387945217

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