边缘
发表于 2025-3-28 16:21:38
Multidimensional Scalinguct A is better than product B”. High-dimensional observations therefore often have mixed data characteristics and contain relative information (w.r.t. a defined standard) rather than absolute coordinates that would enable us to employ one of the multivariate techniques presented so far.
condone
发表于 2025-3-28 20:41:31
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多余
发表于 2025-3-29 01:54:25
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guardianship
发表于 2025-3-29 07:01:33
Wolfgang Karl Härdle,Léopold SimarRevised and updated third edition offers a broader range of material Wide scope of methods and applications, making this a comprehensive treatment of the subject A wealth of examples and exercises – i
无聊的人
发表于 2025-3-29 09:20:53
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COMA
发表于 2025-3-29 14:24:40
A Short Excursion into Matrix Algebranotations used in this book for vectors and matrices. Eigenvalues and eigenvectors play an important role in multivariate techniques. In Sections . and ., we present the spectral decomposition of matrices and consider the maximisation (minimisation) of quadratic forms given some constraints.
LIKEN
发表于 2025-3-29 17:11:59
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CLAP
发表于 2025-3-29 22:54:56
Decomposition of Data Matrices by Factorsvariate or univariate devices used to reduce the dimensions of the observations. In the following three chapters, issues of reducing the dimension of a multivariate data set will be discussed. The perspectives will be different but the tools will be related.
翅膀拍动
发表于 2025-3-30 01:12:59
Canonical Correlation Analysist type of low-dimensional projection helps in finding possible joint structures for the two samples. The canonical correlation analysis is a standard tool of multivariate statistical analysis for discovery and quantification of associations between two sets of variables.
惊呼
发表于 2025-3-30 07:55:12
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