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  • 1
    Electronic Resource
    Electronic Resource
    Statistical F-tests for abstract factor analysis and target testingPresented in the poster session at The Second Hidden Peak Symposium on Computer-Enhanced Analytical Spectroscopy, Snowbird, Utah, 1-3 June 1988. (1989)
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 3 (1989), S. 49-60 
    Details
    ISSN: 0886-9383
    Keywords: Principal component analysis ; Factor analysis ; Singular value decomposition ; Eigenvalue analysis ; Multivariate analysis ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Fisher variance ratio tests are developed for determining (1) the number of statistically significant abstract factors responsible for a data matrix and (2) the significance of target vectors projected into the abstract factor space. F-tests, developed from the viewpoint of vector distributions, are applied to various data sets taken from the chemical literature.
    Additional Material: 3 Tab.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1002/cem.1180030107
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  • 2
    Electronic Resource
    Electronic Resource
    Theory of the distribution of error eigenvalues resulting from principal component analysis with applications to spectroscopic dataPresented on 2 October 1985 in the Symposium on Chemometrics at the 12th Annual FACSS Meeting in Philadelphia, PA. (1987)
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 1 (1987), S. 33-40 
    Details
    ISSN: 0886-9383
    Keywords: Principal component analysis ; Singular value decomposition ; Factor analysis ; Rank determination ; Eigenvector analysis ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: The distribution of error eigenvalues resulting from principal component analysis is deduced by considering the decomposition of an error matrix in which the errors are uniformly distributed. The derived probability function is \documentclass{article}\pagestyle{empty}\begin{document}$$ P(\lambda ^0 _j) = N(r - j + 1)(c - j + 1) $$\end{document} Where λ0j is the jth error eigenvalue, r and c are the numbers of rows and columns in the data matrix, and N is the normalization constant. This expression is tested and validated by investigations involving model data. The distribution function is used to determine the number of factors responsible for various sets of spectroscopic data taken from the chemical literature (including nuclear magnetic resonance, infrared and mass spectra).
    Additional Material: 1 Ill.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1002/cem.1180010106
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  • 3
    Electronic Resource
    Electronic Resource
    Investigation of copper(II)-Ethylenediaminetetraacetate complexation by window factor analysis of ultraviolet spectraPresented at the Eastern Analytical Symposium in Somerset, NJ on 14 November 1992 (1993)
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 7 (1993), S. 89-98 
    Details
    ISSN: 0886-9383
    Keywords: Factor analysis ; Window factor analysis ; Multicomponent analysis ; Ultraviolet spectroscopy ; Cu(II) complexes ; Ethylenediaminetetraacetic acid ; EDTA ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Window factor analysis (WFA) is a self-modeling chemometric technique for obtaining the concentration profiles of components from evolutionary processes such as chromotography, titration and reaction kinetics. By specifying the ‘window’, i.e. the region along the evolutionary axis indigenous to a component, the concentration profile of the component can be obtained without recourse to any information concerning the other components. Mathematical expressions required to perform such computations are derived. The method is applied to the investigation of copper(II) complexation with ethylenediaminetetraacetate (EDTA) by recording and factor analyzing the ultraviolet spectra of aqueous solutions containing a fixed amount of the disodium salt of EDTA and varying amounts of CuCl2. Evidence for four different species of EDTA is obtained. Clues concerning the stoichiometry of the species are garnered from the concentration profiles.
    Additional Material: 5 Ill.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1002/cem.1180070203
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  • 4
    Electronic Resource
    Electronic Resource
    Window factor analysis: Theoretical derivation and application to flow injection analysis data (1992)
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 6 (1992), S. 29-40 
    Details
    ISSN: 0886-9383
    Keywords: Factor analysis ; Window factor analysis ; Multicomponent analysis ; Flow injection analysis ; Self-modeling curve resolution ; Bismuth chloride complexes ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Window factor analysis (WFA) is a self-modeling method for extracting the concentration profiles of individual components from evolutionary processes such as flow injection, chromatography, titrations and reaction kinetics. The method takes advantage of the fact that each component lies in a specific region along the evolutionary axis, called the window. Theoretical equations are derived. The method is used to extract the concentration profiles and spectra of seven bismuth species from data obtained by Gemperline and Hamilton, who injected bismuth perchlorate into a flowing stream of hydrochloric acid.
    Additional Material: 7 Ill.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1002/cem.1180060104
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