Matrix Variate Distributions / Edition 1

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Useful in physics, economics, psychology, and other fields, random matrices play an important role in the study of multivariate statistical methods. Until now, however, most of the material on random matrices could only be found scattered in various statistical journals. Matrix Variate Distributions gathers and systematically presents most of the recent developments in continuous matrix variate distribution theory and includes new results.
After a review of the essential background material, the authors investigate the range of matrix variate distributions, including:

  • matrix variate normal distribution
  • Wishart distribution
  • Matrix variate t-distribution
  • Matrix variate beta distribution
  • F-distribution
  • Matrix variate Dirichlet distribution
  • Matrix quadratic forms
    With its inclusion of new results, Matrix Variate Distributions promises to stimulate further research and help advance the field of multivariate statistical analysis.

"...gathers & systematically presents most of the recent developments in continuous matrix variate distribution theory & includes new results."

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Editorial Reviews

Gathers together recent developments in continuous matrix variate distribution theory, provides an analytical review of the material, and offers new results that will stimulate further research. Assumes familiarity with introductory multivariate statistical analysis and matrix algebra, and includes chapter problems and a glossary. For researchers and graduate students in multivariate statistical analysis and the investigation sciences. Gupta teaches mathematics and statistics at Bowling Green State University. Nagar teaches mathematics at the University of Antioquia, Colombia. Annotation c. Book News, Inc., Portland, OR (
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Product Details

Table of Contents

Matrix Algebra
Jacobians of Transformations
Zonal Polynomials
Hypergeometric Functions of Matrix Argument
LaGuerre Polynomials
Generalized Hermite Polynomials
Notion of Random Matrix Problems
Density Function
Singular Matrix Variate Normal distribution
Symmetic Matrix Variate Normal Distribution
Restricted Matrix Variate Normal Distribution
Matrix Variate Q-Generalized Normal Distribution
Density Function
Inverted Wishart Distribution
Noncentral Wishart Distribution
Matrix Variate Gamma Distribution
Density Function
Inverted Matrix Variate t-Distribution
Disguised Matrix Variate t-Distribution
Restricted Matrix Variate t-Distribution
Noncentral Matrix Variate t-Distribution
Distribution of Quadratic Forms
Density Functions
Related Distributions
Noncentral Matrix Variate Beta Distribution
Density Functions
Related Distributions
Noncentral Matrix Variate Dirichlet Distributions
Density Function
Functions of Quadratic Forms
Series Representation of the Density
Noncentral Density Function
Expected Values
Wishartness and Independence of Quadratic Forms of the Type XAX'
Wishartness and Independence of Quadratic Forms of the Type XAX'+1/2(LX'+XL')+C
Wishartness and Independence of Quadratic Forms of the Type XAX'+L1X'+XL'2+C
Uniform Distribution on Stiefel Manifold
Von Mises-Fisher Distribution
Bingham Matrix Distribution
Generalized Bingham-Von Mises Matrix Distribution
Manifold Normal Distribution
Matrix Angular Central Gaussian Distribution
Bimatix Wishart Distribution
Beta-Wishart Distribution
Confluent Hypergeometric Function Kind 1 Distribution
Confluent Hypergeometric Function Kind 2 Distribution
Hypergeometric Function Distributions
Generalized Hypergeometric Function Distributions
Complex Matrix Variate Distributions
Matrix Variate Liouville Distributions
Matrix Variate Spherical Distributions
Matrix Variate Elliptically Contoured Distributions
Orthogonally Invariant and Residual Independent Matrix Distributions
Each chapter also includes an Introduction and Problems


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