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  • Articles  (1,441)
  • Analytical Chemistry and Spectroscopy  (1,441)
  • 1990-1994  (1,441)
  • 1992  (1,441)
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  • Articles  (1,441)
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  • 1990-1994  (1,441)
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  • 1
    Electronic Resource
    Electronic Resource
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 6 (1992) 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 6 (1992), S. i 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 6 (1992), S. 63-64 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Type of Medium: Electronic Resource
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  • 4
    Electronic Resource
    Electronic Resource
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 6 (1992), S. 65-83 
    ISSN: 0886-9383
    Keywords: Trilinear decomposition ; Receptor modeling ; Source identification ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: In many cases, monitoring data for ambient airborne particles can be organized in the form of a three-way data table with one way for chemical species, one for sampling periods and one for sites. A direct trilinear decomposition followed by a matrix reconstruction (DTDMR) is developed to analyze such a data table as a whole. The three-way data set is composed into three two-way matrices by a direct trilinear decomposition (DTD). The column vectors of each of the matrices are called ‘source profiles’, ‘emission patterns’ and ‘site coefficients’ respectively. Particulate sources are identified by examining both their source profiles and emission patterns. After the sources have been identified, emission patterns and site coefficients are used to produce a three-way matrix that gives estimates of mass contributions of sources to the samples collected at every site in every period. By simulation study, not only has the method been verified, but a good indicator has been found that shows the number of factors (i.e. sources) in the system. Unlike other receptor models, DTDMR does not require source profile data and does not involve trial-and-error procedures. Since DTDMR identifies sources based on variations in two dimensions, it has a higher potential to distinguish two sources that have similar chemical compositions. The DTDMR model has provided excellent results with simulated data and has been applied in a real world three-way data set.
    Additional Material: 7 Ill.
    Type of Medium: Electronic Resource
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  • 5
    Electronic Resource
    Electronic Resource
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 6 (1992), S. 113-116 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Additional Material: 1 Ill.
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  • 6
    Electronic Resource
    Electronic Resource
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 6 (1992), S. 117-118 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Type of Medium: Electronic Resource
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  • 7
    Electronic Resource
    Electronic Resource
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 6 (1992), S. 151-161 
    ISSN: 0886-9383
    Keywords: NIR spectroscopy ; Wavelength selection ; Interaction effects ; Multicomponent mixtures ; Partial least squares ; Generalized least squares ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Modern scanning (near-)infrared reflectance/absorption (NIR) spectroscopes measure the absorptions or reflectances at a sequence of around 1000 wavelengths. Training data may consist of 10-100 carefully designed sample mixtures for which the true composition of the mixture is either known by formulation or accurately determined by wet chemistry. In future one wishes to predict the true composition from the spectrum. In this paper we compare a simple wavelength selection approach with methods which retain all the wavelengths. It offers a powerful yet simple technique for choosing those wavelengths that are specific to each pure component as against the other components (including the medium) for the varying compositions. In the presence of a defined range of ingredients in thus chooses wavelengths which are highly selective for each particular component. It has the added advantage of selecting wavelengths which are little effected by interaction effects and consequent non-linearities.The calibration data used consist of 125 observations of three sugars, each varying at five levels in a full 53 design. The validation set consists of 21 further samples specially selected to have compositions outside the range of the training sample. The selection methods perform much better on this prediction set than methods which retain all the wavelengths, 700 in this case. The leave-one-out cross-validation internal to the calibration data would point to the opposite finding and suggests that such crossvalidations may be overly flattering to techniques such as partial least squares and may encourage overfitting. After selection, simple straightforward least squares methods may be used, eschewing the need for ‘shrinkage’ methods such as partial least squares or ridge regression.
    Additional Material: 4 Ill.
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  • 8
    Electronic Resource
    Electronic Resource
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 6 (1992), S. 247-255 
    ISSN: 0886-9383
    Keywords: Analysis of variance ; Assumptions ; Graphics ; Models ; Validation of model ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: The computer has made it possible to scrutinize data rapidly by means of graphics. This should be done prior to the application of any model to the data, since the model must be validated before using it as a means of analyzing the data. The procedure is illustrated in terms of two examples of real experimental data.
    Additional Material: 5 Ill.
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  • 9
    Electronic Resource
    Electronic Resource
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 6 (1992), S. 284-285 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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  • 10
    Electronic Resource
    Electronic Resource
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 6 (1992), S. 307-334 
    ISSN: 0886-9383
    Keywords: Non-linear PLS ; Quadratic regression ; Non-linear models ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: We treat here an extension of linear PLS regression to include regression on quadratic PLS components. The quadratic regression can be viewed as a natural extention of linear PLS regression to quadratic PLS according to the H-principle of mathematical modelling. The numerical implementation is treated in detail. It is shown that this approach can be used for models with large numbers of variables. Some modelling strategies are discussed depending on the purpose of the modelling. Applications of this approach are treated.
    Additional Material: 12 Ill.
    Type of Medium: Electronic Resource
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