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Kernel Principal Component Analysis
1997A new method for performing a nonlinear form of Principal Component Analysis is proposed. By the use of integral operator kernel functions, one can efficiently compute principal components in highdimensional feature spaces, related to input space by some nonlinear map; for instance the space of all possible d-pixel products in images.
Bernhard Schölkopf +2 more
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Robust Principal Components Regression
2002We consider the multivariate linear regression model with p explanatory variables X and q ≥ 1 response variables Y. Moreover we assume that the regressors are multicollinear. This situation often occurs in the calibration of chemometrical data, where the X-variables correspond with spectra that are measured at many frequencies.
Verboven, S., Hubert, M.
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Segmented principal component transform–principal component analysis
Chemometrics and Intelligent Laboratory Systems, 2005Abstract A new approach to perform Principal Component Analysis (PCA) on very wide matrices is proposed in this work. The procedure is based on an extension of the Principal Component Transform (PCT) concept—the PCT being applied to non-superimposed segments of the data matrix.
António S. Barros, Douglas N. Rutledge
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Which principal components to utilize for principal component regression
Journal of Chemometrics, 1992AbstractPrincipal components (PCs) for principal component regression (PCR) have historically been selected from the top down for a reliable predictive model. That is, the PCs are arranged in a list starting with the most informative (PC associated with the largest singular value) and proceeding to the least informative (PC associated with the smallest
Jon M. Sutter +2 more
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Principal components or principal axes
1999The expression principal components first appeared in the writings of the American statistician Harold Hotelling in 1933, but the technique was known earlier as principal axes and goes back to Karl Pearson (1901). In principle, principal components are appropriate for the analysis of variation within a sample coming from a single statistical population
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1986
The theory and practice of principal components are considered both from the point of view of statistical theory and from that of descriptive statistics. Some well known applications are briefly discussed.
Kloek, T., Kloek, T.
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The theory and practice of principal components are considered both from the point of view of statistical theory and from that of descriptive statistics. Some well known applications are briefly discussed.
Kloek, T., Kloek, T.
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Cross-Validatory Estimation of the Number of Components in Factor and Principal Components Models
Technometrics, 1978Svante Wold
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