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Predictive power of principal components for single-index model and sufficient dimension reduction

✍ Scribed by Artemiou, Andreas; Li, Bing


Book ID
120323737
Publisher
Elsevier Science
Year
2013
Tongue
English
Weight
258 KB
Volume
119
Category
Article
ISSN
0047-259X

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[Lecture Notes in Computational Science
✍ Gorban, Alexander N.; KΓ©gl, BalΓ‘zs; Wunsch, Donald C.; Zinovyev, Andrei Y. πŸ“‚ Article πŸ“… 2008 πŸ› Springer Berlin Heidelberg 🌐 German βš– 731 KB

In 1901, Karl Pearson invented Principal Component Analysis (PCA). Since then, PCA serves as a prototype for many other tools of data analysis, visualization and dimension reduction: Independent Component Analysis (ICA), Multidimensional Scaling (MDS), Nonlinear PCA (NLPCA), Self Organizing Maps (SO