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Matrix Variate Distributions

Gupta, A.K., Nagar, D.K.·2018·Chapman & Hall/CRC eBooks

Abstract

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 distributionWishart distributionMatrix variate t-distributionMatrix variate beta distributionF-distributionMatrix variate Dirichlet distributionMatrix quadratic formsWith its inclusion of new results, Matrix Variate Distributions promises to stimulate further research and help advance the field of multivariate statistical analysis.

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Metadata

Authors
Gupta, A. K., & Nagar, D. K.
Venue
Chapman & Hall/CRC eBooks
Published
2018-05-02
OpenAlex
W3148198191
Cited by
1,295
References
0
Type
reference entry
Language
en
Open access
closed

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CoChat. (2026). Citation check: Matrix Variate Distributions. https://app.cochat.ai/papers/10.1201/9780203749289
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Gupta, A. K., & Nagar, D. K. (2018). Matrix Variate Distributions. Chapman & Hall/CRC eBooks. https://doi.org/10.1201/9780203749289

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.