Overview
- Explores topics in multivariate statistical analysis, relevant in real and complex domains
- Utilizes simplified and unified notations which makes the subject matter accessible and enjoyable
- Features an in-depth treatment of theory with a fair balance of applied coverage
- This book is open access, which means that you have free and unlimited access
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About this book
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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Table of contents (16 chapters)
Authors and Affiliations
About the authors
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.
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.
Bibliographic Information
Book Title: Multivariate Statistical Analysis in the Real and Complex Domains
Authors: Arak M. Mathai, Serge B. Provost, Hans J. Haubold
DOI: https://doi.org/10.1007/978-3-030-95864-0
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s) 2022
Hardcover ISBN: 978-3-030-95863-3Published: 06 October 2022
Softcover ISBN: 978-3-030-95866-4Published: 07 October 2023
eBook ISBN: 978-3-030-95864-0Published: 04 October 2022
Edition Number: 1
Number of Pages: XXVII, 921
Number of Illustrations: 3 b/w illustrations
Topics: Probability Theory and Stochastic Processes, Applications of Mathematics, Statistical Theory and Methods, Complex Systems