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  • Analytical Chemistry and Spectroscopy  (2,202)
  • 1995-1999  (2,202)
Collection
Keywords
Publisher
Years
Year
  • 1
    Electronic Resource
    Electronic Resource
    Expression of the reference value for proficiency tests (1995)
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 9 (1995), S. 197-209 
    Details
    ISSN: 0886-9383
    Keywords: proficiency test ; true value ; homogeneity robust statistic ; standard ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Profficiency tests raise two types of problems: (i) the homogeneity of a sample must be carefully checked before using it as a reference material; (ii) it is necessary to define a conventional reference value (RV) in order to rank participants. Since these topics are poorly addressed in the literature, a reference material was specially prepared in order to propose a procedure for verifying homogeneity and to establish whether the algorithms classically used to compute the conventional true value have an influence on the conclusion of the test.The homogeneity of the sample was not perfect and univariate and multivariate techniques were used to demonstrate some analytes can be suspected as heterogeneous. However, this was considered adequate for introducing the sample in a large proficiency test organized between four laboratory associations which regularly perform such tests. Altogether more than 3000 measurements were collected and eight algorithms were applied to compute the RV on 14 analytes. Thus is was possible to demonstrate that some of these algorithms are better adapted than others. It is also obvious that some analytes are better suited to proficiency testing.It can be concluded from this work that some effort towards standardization would be profitable to check homogeneity or to compute the RV, especially since the economic weight of proficiency testing is becoming even more important with the development of certification accreditation.
    Additional Material: 3 Ill.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1002/cem.1180090306
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  • 2
    Electronic Resource
    Electronic Resource
    Masthead (1995)
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 9 (1995) 
    Details
    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
    URL: http://dx.doi.org/10.1002/cem.1180090601
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  • 3
    Electronic Resource
    Electronic Resource
    Robust non-linear regression analysis (1995)
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 9 (1995), S. 451-457 
    Details
    ISSN: 0886-9383
    Keywords: non-linear regression ; optimization ; robust methods ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Several robust regression methods, including a new proposal, are described and their properties discussed. Resistance to various types of outliers and non-normality is demonstrated. The techniques are applied to non-linear regression models from chemical kinetics and calibration. Optimization of the types of objective functions encountered when applying robust regression is considered.
    Additional Material: 5 Ill.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1002/cem.1180090603
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  • 4
    Electronic Resource
    Electronic Resource
    Incorporating auxiliary predictor variation in principal component regression models (1995)
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 9 (1995), S. 471-481 
    Details
    ISSN: 0886-9383
    Keywords: batch prediction ; continuum regression ; multivariate calibration ; sequential prediction ; simultaneous prediction ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: In analytical chemistry a single fitted calibration model is used repeatedly to predict the level of the analyte of interest for the specimens comprising the prediction set. Unlike the calibration (or training) set, which is often limited in size, the prediction set can be very large.In the case of multivariate calibration a number of methods such as PLS and PCR are commonly used to construct the calibration model. The set of instrumental measurements and the reference analyte level are available for each specimen in the calibration set. For specimens in the prediction set, only the instrumental measurements are available, since the problem is to predict the analyte level for these specimens. It is not widely recognized that predictions of the analyte levels for individual specimens can be improved by utilizing seemingly unrelated information from the instrumental measurements associated with the other members of the prediction set. In the case of PCR there exists a very straightforward procedure for doing this. A description of the various sources of prediction errors is provided to explain the ability of PCR to utilize this additional information. The use of PCR in this context is illustrated with both a synthetic and a real example.
    Additional Material: 1 Ill.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1002/cem.1180090605
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  • 5
    Electronic Resource
    Electronic Resource
    Multivariate analysis in practice: A training package, K. Esbensen, S. Schonkopf and T. Midtgaard, CAMO AIS: Trondheim, 1994,361 pp. ISBN 82-993330-0-8, $295.00. The text is bundled with the training version of the Unscrambler® multivariate analysis software for MS-DOS. Available from CAMO AIS, Olav Tryggvasons Gate 24, N-7011 Trondheim, Norway (Telephone: (+47) 7351 4966 Fax: (+47) 7351 4257) or from CAMO USA, 435 Blake Street, Menlo Park, CA 94025, U.S.A. (TelephoneFax: (+1415) 324-4286, Internet: teledyn@netcom.com) (1995)
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 9 (1995), S. 521-523 
    Details
    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
    URL: http://dx.doi.org/10.1002/cem.1180090609
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  • 6
    Electronic Resource
    Electronic Resource
    A correlation principal component regression analysis of NIR data (1995)
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 9 (1995), S. 21-29 
    Details
    ISSN: 0886-9383
    Keywords: Near-infrared absorbance ; Partial least squares ; Principal component regression ; Root-mean-square error of prediction ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: The use of principal component regression (PCR) as a multivariate calibration method has been discussed by a number of authors. In most situations principal components are included in the regression model in sequence based on the variances of the components, and the principal components with small variances are rarely used in regression. As pointed out by some authors, a low variance for a component does not necessarily imply that the corresponding component is unimportant, especially when prediction is of primary interest. In this paper we investigate a different version of PCR, correlation principal component regression (CPCR). In CPCR the importance of principal components in terms of predicting the response variable is used as a basis for the inclusion of principal components in the regression model. Two typical examples arising from calibrating near-infrared (NIR) instruments are discussed for the comparison of the two different versions of PCR along with partial least squares (PLS), a commonly used regression approach in NIR analysis. In both examples the three methods show similar optimal prediction ability, but CPCR performs better than standard PCR and PLS in terms of the number of components needed to achieve the optimal prediction ability. Similar results are also seen in other NIR examples.
    Additional Material: 2 Ill.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1002/cem.1180090104
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  • 7
    Electronic Resource
    Electronic Resource
    Announcement (1995)
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 9 (1995), S. i 
    Details
    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
    URL: http://dx.doi.org/10.1002/cem.1180090108
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  • 8
    Electronic Resource
    Electronic Resource
    International chemometrics research meeting (ICRM) (1995)
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 9 (1995), S. 137-138 
    Details
    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
    URL: http://dx.doi.org/10.1002/cem.1180090205
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  • 9
    Electronic Resource
    Electronic Resource
    Simple encoding of infrared spectra for pattern recognition. 1: Statistical examination of the effectiveness and information content by factor analysis (1995)
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 9 (1995), S. 143-168 
    Details
    ISSN: 0886-9383
    Keywords: pattern recognition ; infrared spectra ; factor analysis ; maximum likelihood method ; entropy of information ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: The spectral region from 700 to 3600 cm-1 is subdivided into several wave number intervals. The peaks in each interval are summarized by means of three encoding algorithms. Using a factor model of kcommon factors, the total extractable variacnce (com) of a given set of intervals is calculated and correlated with the redundancy of information in all these intervals. The value of com is verified by analysis of the factor loadings aik (factor pattern). Finally, the information content of some chosen sets of intervals coded by the three selected feature algorithms will be correlated to the probability of information flow through a serial-parallel network. The encoding using only wave numbers was found to be the most effective.
    Additional Material: 9 Ill.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1002/cem.1180090303
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  • 10
    Electronic Resource
    Electronic Resource
    Diagnostics statistics in QSAR (1995)
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 9 (1995), S. 211-221 
    Details
    ISSN: 0886-9383
    Keywords: diagnostics statistics ; QSAR ; MASCA ; principal component regression ; non-least squares regression ; types of multicollincarity ; flagged observations ; influential points ; high-leverage points ; outliers ; extra-carrier points ; random perturbation ; cluster correalation ; resampling ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: The formal application of a Hansch analysis to a series of 3-quinuclidinyl benzylates (QNBs) led to a ‘statistically significant’ QSAR equation. In contrast, the application of the MASCA model has shown that the design matrix is unsuitable for each QSAR analysis: one sample member is an outlier but not a high-leverage or influential point; another one is an influential point, a high-leverage point and an extra-carrier point. The regressors of the design matrix are multicollinear without predictive model power. The result of such flagged observation and this type of multicollinearity is a multiple cluster correlation. The QNB series is a good example for ‘sampling artifacts’ where no practically important but artificial QSARs can be found.
    Additional Material: 3 Ill.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1002/cem.1180090307
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