Preferred set selection by iterative key set factor analysis

Abstract The object of preferred set selection is the identification of the minimum set of measurements that best characterizes a multicomponent system. The key set of rows (or columns) of a data matrix is the combination of rows (or columns) most orthogonal to each other. The key set optimizes data reproduction and therefore constitutes the preferred set. This paper describes an iterative refinement of the original key set methodology that ensures the selection of the most orthogonal set of typical vectors. Results of the iterative algorithm are compared with the noniterative procedure using a variety of data sets.

[1]  G. L. Ritter,et al.  Factor analysis of the mass spectra of mixtures , 1976 .

[2]  Wolfhard Wegscheider,et al.  Selectivity in multicomponent analysis , 1986 .

[3]  W. Windig,et al.  Determination of fractional concentrations and exact component spectra by factor analysis of pyrolysis mass spectra of mixtures , 1987 .

[4]  E. A. Sylvestre,et al.  Self Modeling Curve Resolution , 1971 .

[5]  Darryl G. Howery,et al.  Factor analysis of solute parameters in ether-stationary phase interactions , 1975 .

[6]  T. Hirschfeld,et al.  Unique-sample selection via near-infrared spectral subtraction. , 1985, Analytical chemistry.

[7]  Delaney Mf,et al.  Selection of wavelengths for absorbance ratio monitoring in liquid chromatography. , 1987 .

[8]  Delaney Mf,et al.  Selection of representative wavelength sets for monitoring in liquid chromatography with multichannel ultraviolet-visible detection. , 1987 .

[9]  E. R. Malinowski,et al.  Factor analysis for isolation of the Raman spectra of aqueous sulfuric acid components , 1984 .

[10]  G. Puchwein.  Selection of calibration samples for near-infrared spectrometry by factor analysis of spectra , 1988 .

[11]  Edmund R. Malinowski,et al.  Factor analysis of solvent shifts in proton magnetic resonance , 1970 .

[12]  Joel M. Harris,et al.  Selection of analytical wavelengths for multicomponent spectrophotometric determinations , 1985 .

[13]  Edmund R. Malinowski,et al.  Obtaining the key set of typical vectors by factor analysis and subsequent isolation of component spectra , 1982 .

[14]  J. Fiala.  Powder diffraction analysis of a three-component sample , 1980 .

[15]  J. Futrell,et al.  Separation of mass spectra of mixtures by factor analysis , 1979 .

[16]  W. Windig,et al.  Fast self-modeling curve-resolution method for time-resolved mass spectral data , 1988 .

[17]  T. Næs.  The design of calibration in near infra‐red reflectance analysis by clustering , 1987 .

[18]  B. Kowalski,et al.  Quantitative Resolution of Fused Chromatographic Peaks in Gas Chromatography/Mass Spectrometry. , 1982 .

[19]  J. Koenig,et al.  Factor analysis for separation of pure component spectra from mixture spectra , 1983 .

[20]  J. Scrivens,et al.  Isolation of component spectra in the analysis of mixtures by mass spectrometry and 13C nuclear magnetic resonance spectroscopy: The utility of abstract factor analysis , 1987 .