Multivariate statistical analysis in the real and complex domains
著者
書誌事項
Multivariate statistical analysis in the real and complex domains
Springer, c2022
- : hbk
大学図書館所蔵 件 / 全3件
-
該当する所蔵館はありません
- すべての絞り込み条件を解除する
内容説明・目次
内容説明
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.
目次
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.
「Nielsen BookData」 より
