Multivariate Statistical Analysis in the Real and Complex Domains

Arak M. Mathai, Serge B. Provost, Hans J. Haubold (Autoren)

Buch | Hardcover

XXVII, 921 Seiten

2022 | 1st ed. 2022
Springer International Publishing (Verlag)
978-3-030-95863-3 (ISBN)

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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.

lt;b>Dr. A.M. Mathai is professor emeritus at McGill University and visiting professor at many other universities around the world. He has published over 37 books and over 300 research articles. Dr. Mathai has been invited to speak at conferences, universities, and other institutes around the world. His areas of research include applied statistics, probability, and mathematical statistics.
Dr. Serge B. Provost is professor at the University of Western Ontario. His research interests include multivariate analysis, computational statistics and distribution theory, with applications involving problems arising in various areas of scientific investigations such as biostatistics, finance, optics, imaging, and machine learning. Dr. Provost has received three teaching awards and chaired a national fellowship and scholarship selection committee. He is a fellow and chartered statistician of the Royal Statistical Society.
Dr. Hans J. Haubold is professor of theoretical astrophysics at the Office for Outer Space Affairs of the United Nations. His research interest focuses on the internal structure of the sun, solar neutrinos, and special functions of mathematical physics. He is also interested in the history of astronomy, physics, and mathematics, specifically Einstein's and Michelson's contributions to theoretical and experimental physics. Dr. Haubold is a member of the American Astronomical Society, the American Mathematical Society, and the History of Science Society.

1. Mathematical Preliminaries.- 2. The Univariate Gaussian and Related Distribution.- 3. Multivariate Gaussian and Related Distributions.- 4. The Matrix-variate Gaussian Distribution.- 5. Matrix-variate Gamma and Beta Distributions.- 6. Hypothesis Testing and Null Distributions.- 7. Rectangular Matrix-variate Distributions.- 8. Distributions of Eigenvalues and Eigenvectors.- 9. Principal Component Analysis.- 10. Canonical Correlation Analysis.- 11. Factor Analysis.- 12. Classification Problems.- 13. Multivariate Analysis of Variance (MANOVA).- 14. Profile Analysis and Growth Curves.- 15. Cluster Analysis and Correspondence Analysis.

Erscheinungsdatum	07.10.2022
Zusatzinfo	XXVII, 921 p. 3 illus.
Verlagsort	Cham
Sprache	englisch
Maße	210 x 279 mm
Gewicht	2540 g
Themenwelt	Mathematik / Informatik ► Informatik ► Theorie / Studium
	Mathematik / Informatik ► Mathematik ► Statistik
	Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik
Schlagworte	classifications • Cluster • complex domain • Factor Analysis • Gaussian distributions • Mathematical Statistics • matrix-variate • Multivariate Statistical Analysis • open access • profile analyses • type-1 distributions • type-2 distributions • Wishart Distribution
ISBN-10	3-030-95863-9 / 3030958639
ISBN-13	978-3-030-95863-3 / 9783030958633
Zustand	Neuware