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Multivariate Statistical Analysis in the Real and Complex Domains

This book explores topics in multivariate statistical analysis, relevant in the real and complex domains. It utilizes simplified and unified notations to render the complex subject matter both accessible and enjoyable, drawing from clear exposition and numerous illustrative examples. The book featur...

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Main Authors: Mathai, Arak M., Provost, Serge B., Haubold, Hans J.
Formato: Online
Idioma:inglés
Publicado: Springer Nature 2022
Subjects:
multivariate statistical analysis
mathematical statistics
complex domain
matrix-variate
Gaussian distributions
Wishart distribution
type-1 distributions
type-2 distributions
factor analysis
classifications
cluster
profile analyses
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematics
thema EDItEUR::P Mathematics and Science::PH Physics::PHS Statistical physics
Acceso en liña:ONIX_20221118_9783030958640_49
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Summary:This book explores topics in multivariate statistical analysis, relevant in the real and complex domains. It utilizes simplified and unified notations to render the complex subject matter both accessible and enjoyable, drawing from clear exposition and numerous illustrative examples. The book features an in-depth treatment of theory with a fair balance of applied coverage, and a classroom lecture style so that the learning process feels organic. It also contains original results, with the goal of driving research conversations forward. This will be particularly useful for researchers working in machine learning, biomedical signal processing, and other fields that increasingly rely on complex random variables to model complex-valued data. It can also be used in advanced courses on multivariate analysis. Numerous exercises are included throughout.

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