Multivariate Statistical Analysis in the Real and Complex Domains
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49 924 Ft
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Product details:
- Edition number 1st ed. 2022
- Publisher Springer
- Date of Publication 7 October 2023
- Number of Volumes 1 pieces, Book
- ISBN 9783030958664
- Binding Paperback
- No. of pages921 pages
- Size 279x210 mm
- Weight 2300 g
- Language English
- Illustrations 3 Illustrations, black & white 543
Categories
Short description:
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.
Long description:
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.
Table of Contents:
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.
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Multivariate Statistical Analysis in the Real and Complex Domains
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