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  • Articles  (1,605)
  • Analytical Chemistry and Spectroscopy  (1,605)
  • 2020-2022
  • 1995-1999  (1,605)
  • Chemistry and Pharmacology  (1,605)
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  • Articles  (1,605)
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  • 11
    Electronic Resource
    Electronic Resource
    Interactive variable selection (IVS) for PLS. Part II: Chemical applications (1995)
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 9 (1995), S. 331-342 
    Details
    ISSN: 0886-9383
    Keywords: partial least squares (PLS) ; variable selection ; IVS-PLS ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: With the aim of developing PLS models with improved predictive properties, an interactive variable selection (IVS) approach for PLS regression was introduced in Part I of this series. IVS-PLS is based on a dimension-wise selective removal of single elements in the PLS weight vector w. IVS uses cross-validation (CV) as a guiding tool. The present paper illustrates the use of IVS-PLS on both simulated data and real examples from chemistry. In the first example, spectrophotometric data were simulated according to an experimental design. The objective was to see how IVS-PLS was influenced by different levels of noise in X and Y and by the number of predictor variables (K). The results of the modelling are shown as response surfaces. In addition, four real examples were modelled by the IVS-PLS technique. The real data sets were chosen to reflect different types of data from chemistry. For each example a comparison of ‘prediction error sum of squares’ (PRESS) between IVS-PLS and classical PLS is madeFor most of the examples containing many predictor variables IVS-PLS shows an improvement in predictive properties over classical PLS. Also, improvements for IVS-PLS2 (modelling of more than one y-variable) models were found. For data sets with a moderate number of variables the influence of the IVS method becomes less pronounced.
    Additional Material: 3 Ill.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1002/cem.1180090502
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  • 12
    Electronic Resource
    Electronic Resource
    An extended strategy for exploratory multivariate image analysis including noise considerations (1995)
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 9 (1995), S. 389-409 
    Details
    ISSN: 0886-9383
    Keywords: multivariate image analysis ; principal component analysis ; exploratory data analysis ; projection in multivariate space ; graphical visualization ; noise ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Multivariate image analysis (MIA) is a powerful tool for many image segmentation and classification problems, but the interpretation and understanding of the original and resulting multidimensional (multivariate) data are not always easy. A strategy for MIA has been proposed which describes its usage on multivariate images for segmentation tasks. MIA starts with principal component analysis (PCA) and then continues with interactive analysis of the output from PCA. In this paper a number of extensions to MIA are proposed. The extensions are the suggestion to incorporate preprocessing of the multivariate image in MIA, the suggestion to use synthetic multivariate image models which create a clear-cut situation, and new visualization tools which improve the interactivity and understanding of the results. Extended MIA is applied on synthetic multivariate image data simulating a possible application with large noise, positron emission tomography (PET). As a result of the interactive analysis, suggestions for preprocessing emerge. The developed methodology for handling the noise is then applied on real PET image data with good results.
    Additional Material: 20 Ill.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1002/cem.1180090506
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  • 13
    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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  • 14
    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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  • 15
    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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  • 16
    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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  • 17
    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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  • 18
    Electronic Resource
    Electronic Resource
    Stone and jonathan versus mager debate (1995)
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 9 (1995), S. 230-231 
    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.1180090311
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  • 19
    Electronic Resource
    Electronic Resource
    A review of robust process design approaches (1995)
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 9 (1995), S. 239-262 
    Details
    ISSN: 0886-9383
    Keywords: industrial experimentation ; parameter design ; quality by design ; robust design ; Taguchi method ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: The aim of this paper is to present a simple structured review of the different approaches to robust process design to clarify their similarities and dissimilarities. It is primarily written for practitioners who wish to understand and compare the main ideas of each approach and to apply them to their work. Two examples are used to illustrate the different approaches and their corresponding data analysis strategies: the first one is a constructed example on a pigment kneading process and the second one is real example dealing with the validation of an HPLC method. A comparison of the different approaches is provided and some practical recommendations are formulated.
    Additional Material: 12 Ill.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1002/cem.1180090402
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  • 20
    Electronic Resource
    Electronic Resource
    PLS shrinks (1995)
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 9 (1995), S. 323-326 
    Details
    ISSN: 0886-9383
    Keywords: partial least squares ; biased regression ; ordinary least squares ; minimum length least squares ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: An algebraic proof is given that in partial least squares (PLS) regression the Euclidean length of the estimator is shrunk in comparison with the ordinary least squares estimator or with PLS estimators based on a larger number of dimensions.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1002/cem.1180090406
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