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  • Analytical Chemistry and Spectroscopy  (12,160)
  • 1995-1999  (2,202)
  • 1985-1989  (5,640)
  • 1980-1984  (4,318)
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  • 1
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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  • 2
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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  • 3
    Electronic Resource
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    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 9 (1995), S. 229-229 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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  • 4
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    Journal of Chemometrics 9 (1995), S. 230-231 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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  • 5
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    Journal of Chemometrics 9 (1995), S. 232-236 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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  • 6
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    Journal of Chemometrics 9 (1995), S. 343-362 
    ISSN: 0886-9383
    Keywords: straight line calibration ; errors in both axes ; uncertainties ; linear regression ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Calibration is a fundamental step in the calculation of the unknown concentration of analyte in most analytical methods. It is known that for certain methodologies, if only the errors in the independent variable are taken into account, there may be considerable errors in the estimation of the value of the regression coefficients, the derived statistical parameters and in some cases the sought for response and concentration values. This paper reviews the calibration methods including some references to procedures for the detection of outliers and robust regression when there are errors in both axes. The advantages and limitations of the different approaches are discussed and a comparative study is made of the approaches of several techniques for which computer programmes have been developed based on the algorithms put forward by the different authors. Finally, some trends of future development in this field are envisaged.
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  • 7
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    Journal of Chemometrics 9 (1995), S. 363-372 
    ISSN: 0886-9383
    Keywords: PLS regression ; orthogonal expansion ; optimization ; Lagrange multipliers ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: A simple iteration algorithm that is faster and less memory-intensive than the NIPALS iteration algorithm for PLS regression is presented. The iteration algorithm is obtained by treating the orthogonal expansion or decomposition of a matrix X as an extremum problem subject to normalization and orthogonality constraint conditions and then solving the problem by use of the method of Lagrange multipliers. The main idea in this method is to find the transformation vector r. The latent variable t is expressed exactly as the linear combination of X-variables with the vector r so that the final regression coefficients can be conveniently provided. In the algorithm the recursion of the orthogonal projection is needed, which is derived by use of a matrix inverse formula. Algorithms are established from the equation for calculating the vector r that are suitable for dealing with three cases of large data sets. The first case is when the number of objects is very large, the number of variables is relatively small and the number of Y-variables is equal to or greater than the number of X-variables. The second case is when the number of objects is very large, the number of variables is relatively small and the number of X-variables is greater than the number of Y-variables. The last case is when the number of variables, either X- or Y-variables, or both, is very large and the number of objects is small.
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  • 8
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    Journal of Chemometrics 9 (1995), S. 431-432 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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  • 9
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    Journal of Chemometrics 9 (1995), S. 451-457 
    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.
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  • 10
    ISSN: 0886-9383
    Keywords: PLS ; kernel algorithm ; multivariate calibration ; EM algorithm ; cross-validation ; missing data ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: This is Part II of a series concerning the PLS kernel algorithm for data sets with many variables and few objects. Here the issues of cross-validation and missing data are investigated. Both partial and full crossvalidation are evaluated in terms of predictive residuals and speed and are illustrated on real examples. Two related approaches to the solution of the missing data problem are presented. One is a full EM algorithm and the second a reduced EM algorithm which applies when the number of missing values is small. The two examples are multivariate calibration data sets. The first set consists of UV-visible data measured on mixtures of four metal ions. The second example consists of FT-IR measurements on mixtures consisting of four different organic substances.
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  • 11
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    Journal of Chemometrics 9 (1995), S. 439-439 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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  • 12
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    Journal of Chemometrics 9 (1995) 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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  • 13
    ISSN: 0886-9383
    Keywords: sequential response surface modelling ; Williamson ether synthesis ; SN2 ; optimization ; reaction kinetics ; reaction mechanism ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: In this work the utility of a new method for determining kinetic parameters by sequential response surface modelling, previously described (Part 1), is shown by applying it to an experimental study of a reaction with known kinetics. The nucleophilic substitution reaction between ethoxide and benzyl chloride, the Williamson ether synthesis, was selected as a model reaction. This reaction is known to proceed with second-order kinetics. The method gives access to estimates of initial reaction rate which can be further used to obtain estimates of activation energy and reaction order of reactants. The results obtained are in good agreement with the estimated values of these parameters obtained with conventional kinetic experiments.
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  • 14
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    Journal of Chemometrics 9 (1995), S. 483-487 
    ISSN: 0886-9383
    Keywords: fractional factorial design ; multiresponse ; PLS ; PCA ; reduced-rank regression ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: This paper presents an interpretation of PLS applied to orthogonal explanatory variables. In particular, it is shown that in fractional factorial multiresponse experiments PLS2 gives identical results to ordinary least squares applied to principal components of the response variables. The general relationship is that the reduced-rank regression algorithm which first projects Y onto the X-space and then truncates this matrix by principal component analysis before performing ordinary least squares estimation gives the same predictor as PLS2 and SIMPLS if all the non-zero eigenvalues of XTX are identical.
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  • 15
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    Journal of Chemometrics 9 (1995), S. 471-481 
    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.
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  • 16
  • 17
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    Journal of Chemometrics 9 (1995), S. 531-531 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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  • 18
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    Journal of Chemometrics 9 (1995), S. 509-520 
    ISSN: 0886-9383
    Keywords: canonical variates ; discriminant analysis ; partial least squares ; principal components ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: A new set of derived variables is proposed for exhibiting group separation in multivariate data on for preprocessing such data prior to discriminant analysis. The technique combines optimal features of canonical variate analysis and principal component analysis: the derived variables are linear combinations of the original variables that optimize the canonical variate criterion (ratio of between-group to within-group variance) but subject to the orthogonality constraints of principal components. In this formulation the canonical variates can be derived even when the within-group matrix is singular (i.e. when there are more variables than objects in the data matrix). A simple computational algorithm for extraction of these variables is proposed. The methods are illustrated on several data sets and compared with alternative techniques such as principal component analysis and partial least squares.
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  • 19
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    Journal of Chemometrics 9 (1995), S. 489-507 
    ISSN: 0886-9383
    Keywords: QSAR ; partial least squares ; robust regression ; CoMFA ; weighted regression ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: A robust implementation of partial least squares (PLS) is developed in which the method of iteratively reweighted least squares is adapted for use with PLS. The result is a PLS algorithm which is robust to outliers and is easy to implement. Examples and case studies are presented, followed by two Monte Carlo studies designed to explore the behavior of the method.The paper begins with the motivation and intended applications for the procedure. A discussion is given of the method of interatively reweighted least squares (IRLS) for outlier detection. The procedure, given the name IRPLS, is then presented. Three case studies illustrate how the procedure works on various types of data and how it should be used. The first Monte Carlo study is designed to determine whether the IRPLS procedure correctly identifies multiple outliers in a wide variety of configurations. The second Monte Carlo study is designed to estimate the breakdown bound of the procedure.
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  • 20
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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  • 21
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    Journal of Chemometrics 9 (1995), S. 309-322 
    ISSN: 0886-9383
    Keywords: simulated annealing ; messy genetic algorithms ; optimization of multimodal objective functions ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: The method of simulated annealing is modified so that the concept of messy chromosomes is applied. Constituent genes of messy chromosomes are specified by their respective names (indices) and values (alleles) simultaneously. Unlike simple chromosomes (binary vectors), messy chromosomes may be either under- or overspecified with respect to the problem being solved. The messy simulated annealing algorithm is a very robust and efficient stochastic optimization method which is able to find correct minima of deceptive or highly multimodal objective functions. This is shown by way of a number of simulations.
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  • 22
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    Journal of Chemometrics 9 (1995), S. 323-326 
    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.
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  • 23
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    Journal of Chemometrics 9 (1995), S. 329-330 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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  • 24
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    Journal of Chemometrics 9 (1995) 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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  • 25
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    Journal of Chemometrics 9 (1995), S. 389-409 
    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.
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  • 26
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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  • 27
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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  • 28
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    Journal of Chemometrics 1 (1987) 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
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  • 29
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    Journal of Chemometrics 1 (1987), S. 75-75 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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  • 30
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    Journal of Chemometrics 1 (1987), S. 74-74 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Topics: Chemistry and Pharmacology
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  • 31
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    Journal of Chemometrics 1 (1987), S. 77-77 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
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  • 32
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    Journal of Chemometrics 1 (1987), S. 79-90 
    ISSN: 0886-9383
    Keywords: Numerical deconvolution ; Peak resolution ; Peak separation ; Iterative deconvolution ; Jansson's method ; Super-resolution ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Severely overlapped gas chromatographic peaks can be resolved using Jansson's method. Jansson's method is an iterative nonlinear deconvolution technique and consists of Van Cittert's algorithm with the relaxation factor a function of the kth estimate of the peak shape. The maximum peak amplitude of the instrument and peak non-negativity serve as constraints to improve the peak estimate. Super-resolution is achieved without significantly degrading the chromatogram signal-to-noise ratio. The method only requires a knowledge of the instrument impulse response function and maximum peak height.
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  • 33
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    Journal of Chemometrics 1 (1987), S. 111-120 
    ISSN: 0886-9383
    Keywords: Principal component analysis ; Submatrix analysis ; Spectroscopy ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: In the treatment of spectroscopic data by principal component analysis, correct determination of the dimensionality of the data is essential. Submatrix analysis, which involves preliminary analysis of subsets of the data matrix, is described, and shown to be valuable in determining both the size of the factor space and estimates of equilibrium constants in the system, even for data containing abnormally large experimental error.
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  • 34
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    Journal of Chemometrics 1 (1987), S. 91-101 
    ISSN: 0886-9383
    Keywords: Factor analysis ; Retention indices ; Model ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Retention indices for 18 monomeric stationary-phase solvents and 33 organic solutes are factor analyzed. Six factors reproduce the data matrix near experimental error. The solvents diglycerol and zonyl E-7 are shown to be highly unique, whereas none of the solutes behaves uniquely. Combination sets of solvent vectors and of solute vectors from the data matrix lead to models having errors within experimental error. Basic factors which might influence the solute - solvent interactions are identified by the least-squares method of target testing. For the solvents, a number of properties, including McReynolds' constants and molecular weight, test successfully. For the solutes, carbon number and group dipole moment are representative properties which test successfully. The best combination of solvent basic factors gives errors about twice the experimental error. Combination sets composed only of McReynolds' constants do not model the data well.
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  • 35
    ISSN: 0886-9383
    Keywords: NIR ; Fast Fourier transform ; Principal component analysis ; Discrimination ; Baking quality ; Wheat ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Digitalized continuous near infra-red reflectance (NIR) spectra are composed of a great number of data which must be reduced for microcomputer mathematical treatment. The sequence ‘fast Fourier transform preceding principal component analysis’ was tested to perform data size reduction without a large loss of information. The method was applied on a collection of wheat spectra composed of 351 data. Ten resulting data, which described 99.5% of the total variance, were kept. The relevance of the method was estimated by the ability of the resulting data (i) to regenerate the original signal, and (ii) to discriminate the baking quality of the wheat by stepwise multiple discriminant analysis. The average difference between initial and regenerated spectra was -2.4 × 10-3 log (1/R) units and the standard deviation was 1.16 × 10-3 log (1/R) units. The discrimination treatments gave 89.9% of well classified samples for the calibration test and 90.5% for the prediction test. The application of these mathematical treatments to other continuous signals is discussed.
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    Journal of Chemometrics 1 (1987), S. 135-135 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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  • 37
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    Journal of Chemometrics 1 (1987) 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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  • 38
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    Journal of Chemometrics 1 (1987), S. 1-2 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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  • 39
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    Journal of Chemometrics 1 (1987), S. 3-6 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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  • 40
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    Journal of Chemometrics 2 (1988), S. 67-79 
    ISSN: 0886-9383
    Keywords: Experimental design ; Multivariate calibration ; Variable selection ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Methods of multivariate calibration use models that relate spectral data or sensor array responses to the concentrations of analytes. The goal is to insure that the calibration model can accurately estimate analyte concentrations in unknown samples not contained in the calibration set. The sensors or spectral channels (e.g. wavelengths) selected for incorporation in the model, as well as the samples selected for the calibration step, are known to have an effect on the accuracy of analysis for unknown samples. This work provides a fundamental treatment of this effect and derives criteria for optimal selection. Additionally, a proof is given for the advantage of having more sensors and calibration samples than analytes - the overdetermined case.
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  • 41
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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  • 42
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 1 (1987), S. 250-254 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 2 (1988) 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 2 (1988), S. i 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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  • 46
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    Journal of Chemometrics 2 (1988), S. 1-10 
    ISSN: 0886-9383
    Keywords: Linear discriminant functions ; Pattern recognition ; Monte Carlo simulations ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: In applications of pattern recognition techniques to problems in chemical fingerprinting, only limited knowledge about the underlying statistical distribution of the data is generally available. This means that non-parametric methods must be used. Non-parametric discriminant functions have been used to provide insight into relationships contained within sets of chemical measurements. However, classification based on random or chance separation can be a serious problem. Monte Carlo simulation studies have been carried out to assess the probability of chance classification for non-parametric linear discriminants. The level of expected chance classification is a function of the number of observations (the number of samples), the dimensionality of the problem (the number of independent variables per observation), class membership distribution and the covariance structure of the data being examined. An approach for assessing the level of significance of classification scores obtained from real training sets will be presented. These simulation studies establish limits on the approaches that can be taken with real data sets so that chance classification are improbable, and provide information necessary for integrating the data analysis into the overall experimental design.
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  • 47
    ISSN: 0886-9383
    Keywords: Oligosaccharides ; Glycoproteins ; Identification ; Substructure analysis ; High-resolution ; 1H-NMR spectra ; Computer retrieval ; Reproducibility ; Chemical shifts ; Similarity index ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Based on a statistical model of the reproducibility of NMR spectral features, a system for computer retrieval of high-resolution 1H-NMR spectra of glycoprotein carbohydrates has been developed. For corresponding peaks in an unknown and a reference spectrum, a similarity index based on the reproducibility of the chemical shifts is calculated. In addition, a second similarity index, based on the probability distribution of the percentage of non-matching peaks, has been developed. From these two similarity indices, a combined similarity index using the recall-reliability function as the optimizing criterion has been derived.First results indicate that the ‘1H-NMR reproducibility-based retrieval’ (‘1HRR’) system offers good perspectives for both identification and substructure analysis.
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    Journal of Chemometrics 3 (1989), S. 431-441 
    ISSN: 0886-9383
    Keywords: Resolution of mixtures ; Excitation-emission matrices ; Eigenanalysis ; Wavelength component vectorgram ; Total luminescence spectroscopy ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: We consider the problem of resolving the total luminescence spectra of two-component mixtures. Non-negativity of the constituent spectra is commonly used as a criterion to accomplish this resolution, but its application seldom leads to unique answers. Sometimes, the condition must be relaxed because no solution satisfying non-negativity exists. In these cases judgments must be made concerning which parts of the spectra will be allowed to go negative and by how much.The wavelength component vectorgramn (WCV) is presented here as a tool for assisting the experimenter in making these judgments. Even when non-negative resolutions exist, it may happen that resolutions with slight negative elements will more closely match the spectra of the pure constituents. The WCV can also be used as a tool for detecting these cases. The methodology is illustrated with real data from a two-component mixture.
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    Journal of Chemometrics 3 (1989), S. 453-453 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 3 (1989), S. 451-452 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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  • 51
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    Journal of Chemometrics 3 (1989), S. 443-449 
    ISSN: 0886-9383
    Keywords: Multicomponent analysis ; Iterative refinement ; Simplex method ; Condition numbers ; Linear programming ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Concentration estimates of components present in a sample mixture can be obtained using matrix mathematics. In the past, the condition number of the calibration matrix has been used to give an amplification factor by which uncertainties in data can work through to errors in the concentration estimates. This paper explores an additional interpretation of condition numbers with regards to significant figures and rounding errors. A procedure is suggested which will always give the most accurate concentration estimates provided the calibration matrix is not too ill-conditioned. Condition numbers have also been used by analytical chemists to discuss the error bounds for concentration estimates. Unfortunately, only one representative error bound can be approximated for all the components. This paper will show how to compute bounds for individual concentration estimates obtained as solutions to a system of m equations and n unknowns. The procedure is appropriate when calibration data and sample responses are inaccurate.
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 3 (1989) 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 3 (1989), S. 21-32 
    ISSN: 0886-9383
    Keywords: Kalman filter ; Multicomponent analysis ; Fluorescence spectral shifts ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: The effect of peak shifts on the performance of a Kalman filter multicomponent analysis algorithm has been investigated. A series of Gaussian test systems were employed to characterize the concentration estimation errors and the morphology of the on-line residuals (the innovations sequence). Both forward and reverse filters were used in the generation of the innovations sequences. It was found that the difference between the forward and reverse innovations sequences gave an accurate indication of the direction and magnitude of the peak shift. A series of overlapped two-component systems were also investigated. Again, a correlation between the difference innovations and the degree of the response shift was observed. The behavior of the Kalman filter in fitting the shifted fluorescence emission spectrum of benzo[a]pyrene was also examined. The response for benzo[a]pyrene in cyclohexane solution was compared to that obtained on the surface surface of a reversed phase thin layer chromatography plate. A red shift of 4 nm was detected for the surface spectrum by observing the difference innovations sequence. This approach holds promise for correction of response shifts in multicomponent systems.
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    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.
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  • 56
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    Keywords: Parameter estimation ; Cyclic voltammetry ; Quasi-reversible electron transfer reactions ; Cerium (IV) bis(octaethylporphyrinate) ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Values of the peak potential, the peak current function and the peak potential difference are extracted from simulated cyclic voltammograms of a quasi-reversible electron transfer reaction. Variations of the feature values are described by empirical functions of the model parameters α (transfer coefficient) and ψ′ (dimensionless form of the heterogeneous electron transfer rate constant ks) using multiple linear regression. These functions are used to determine the system parameters α and ks from test data sets of feature values. The predictive power of the features is discussed. It is shown that several features can be used simultaneously in the analysis. Also, α, ks, the formal potential E0 and the diffusion coefficient D can be estimated simultaneously. Experimental data from the metal-centered one-electron reduction of cerium (IV) bis(octaethylporphyrinate), Ce(OEP)2, are analyzed using the technique, and values of the system parameters for this electrochemical reaction are determined.
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 2 (1988), S. 247-263 
    ISSN: 0886-9383
    Keywords: Calibration ; Tensor ; Multivariate ; PCR ; MLR ; PLS ; Regression ; Multidimensional arrays ; Order ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Many analytical instruments now produce one-, two- or n-dimensional arrays of data that must be used for the analysis of samples. An integrated approach to linear calibration of such instruments is presented from a tensorial point of view. The data produced by these instruments are seen as the components of a first-, second- or nth-order tensor respectively. In this first paper, concepts of linear multivariate calibration are developed in the framework of first-order tensors, and it is shown that the problem of calibration is equivalent to finding the contravariant vector corresponding to the analyte being calibrated. A model of the subspace spanned by the variance in the calibration must be built to compute the contravarian vectors. It is shown that the only difference between methods such as least squares, principal components regression, latent root regression, ridge regression and partial least squres resides in the choice of the model.
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    Journal of Chemometrics 2 (1988), S. 265-280 
    ISSN: 0886-9383
    Keywords: Calibration ; Tensor ; Multivariate ; Order ; Regression ; Generalized rank annihilation ; GRAM ; Multi order ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Tensorial calibration provides a useful approach to calibration in general. For calibration of instruments that produce two-dimensional (second-order) arrays of data per sample, tensoial concepts are as natural a way of solving the calibration problem as vectorial concepts are for the multivariate problem. Similarly, for third- and higher-order data, the tensorial description of calibration is also useful. This paper introduces second-order calibration from a tensorial point of view. Univariate, multivariate and bilinear approaches to calibration are presented. The generalized rank annihilation method (GRAM) is described from the tensorial perspective, and it is shown that GRAM is equivalent to finding a second-order tensorial base that spans both tensors (calibration and unknown) with respective diagonal component matrices. GRAM uses a single calibration sample for multicomponent analysis even in the presence of interference. Second-order bilinear calibration is extended to multiple calibration samples where the effect of collinearities is reduced.
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    Journal of Chemometrics 9 (1995), S. 3-20 
    ISSN: 0886-9383
    Keywords: Deconvolution algorithms ; Instrumental analysis ; Spectrometry ; Chemistry ; Analytical Chemistry and Spectroscopy
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    Topics: Chemistry and Pharmacology
    Notes: Deconvolution algorithms for measurand reconstruction are considered. Their metrological and numerical properties are briefly characterized. Six algorithms most frequently used for instrumental applications are selected for closer analysis. Their comparative study is based on the use of spectrometric-type synthetic data, calorimetric-type synthetic data and spectrometric real-world data. Conclusions concerning computational complexity and accuracy of the compared algorithms as well as their metrological applicability are drawn.
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    Journal of Chemometrics 9 (1995), S. 67-68 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 9 (1995), S. i 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 9 (1995) 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 9 (1995) 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 9 (1995), S. 125-135 
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    Keywords: Procrustean analysis ; FT-IR spectroscopy ; NIR spectroscopy ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Procrustean methods allow the fitting of a given matrix to another given matrix observed on the same objects. In the traditional approach orthogonal constraints are imposed upon the transformation matrix, whereas in the alternative approach Procrustean analysis may be performed without such constraints. The two methods (with and without constraints) were compared on data dealing with mid- and near-infrared spectra of oil. The aim was to reconstruct the mid-infrared spectral information using data from the near-infrared spectra. Unconstrained Procrustean analysis proved to be the more efficient for both the calibration and verification sets. Furthermore, the analysis of the transformation matrix between the two infrared ranges made it possible to indicate wavelengths and wave numbers corresponding to the same chemical groups.
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    Journal of Chemometrics 9 (1995), S. 139-141 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 9 (1995), S. 1-2 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 1 (1987), S. 136-136 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 1 (1987) 
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    Journal of Chemometrics 1 (1987), S. 137-137 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 1 (1987), S. 139-155 
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    Keywords: Chemical information systems ; Machine-readable structure representation ; Registration search ; Structure search ; Substructure search ; Chemistry ; Analytical Chemistry and Spectroscopy
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    Topics: Chemistry and Pharmacology
    Notes: This paper decribes the development and current state-of-the-art in computerized systems for the storage and retrieval of chemical structure information. The main types of machine-readable structure representation  -  fragmentation codes, linear notations and connection tables  -  are described, together with the retrieval algorithms which are used to provide structure and substructure search facilities. Current research work in chemical structure retrieval includes the development of techniques for the representation and searching of the generic structures which occur in chemical patents, for searching files of three-dimensional structures, for ranking searches designed to identify compounds structurally similar to a given query compound, and the use of parallel computers to increase the efficiency of substructure searching. Chemical structure handling techniques are also applicable in a range of application areas, including chemical reaction indexing, computer-aided synthesis design and structure elucidation, and substructural analysis methods for the study of quantitative structure - activity relationships.
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    Journal of Chemometrics 1 (1987), S. 157-173 
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    Keywords: Gas chromatography ; Simplex ; Barycentric co-ordinates ; Discriminant analysis ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: This paper proposes an elegant, yet straightforward, model for classifying linear mixtures. A linear mixture is defined as a random vector y in which the variable are a (non-negative) weighted average of corresponding variables, assumed to characterize g component groups. These weights are referred to as ‘mixing proportions’. The model seeks to identify the mixture constituents and estimate the mixing proportions. It is demonstrated within the context of high resolution gas chromatography and the problem of identifying the constituents in polychlorinated biphenyl mixtures.
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    Journal of Chemometrics 1 (1987), S. 175-183 
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    Keywords: Deconvolution ; Jansson's method ; Peak resolution ; Numerical deconvolution ; Super resolution ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: In a previous paper,1 Jansson's method was used to deconvolve overlapped gas chromatographic peaks. It was found that this method gave improved performance over conventional techniques such as perpendicular drop and shoulder quantitation.2,3 This paper will present the results of a comprehensive test of Jansson's method using several sample mixtures. These results will be compared to what can be obtained by using shoulder quantitation, perpendicular drop or an instrument with a longer column. A relatively large number of tests will be performed for each of the four mentioned methods of peak resolution, so there will be a reasonable statistical basis for the goodness of Jansson's method to resolve fused gas chromatographic peaks for a given set of instrument conditions. A brief review of Jansson's method and the modeling of a gas chromatographic process will also be presented.
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    Journal of Chemometrics 1 (1987), S. 201-219 
    ISSN: 0886-9383
    Keywords: Multivariate ; Calibration ; PLS ; Regression ; Spectroscopy ; Selectivity ; Outliers ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: This paper illustrates some advantages of indirect multivariate calibration over conventional calibration: selectivity enhancement and outlier detection. Partial least squares (PLS) calibration is applied for quantitative analysis in the presence of interferences that would make both conventional single-wavelength calibration and direct multicomponent analysis impossible. The PLS algorithm is illustrated graphically, and the importance of outlier detection is demonstrated.
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    Journal of Chemometrics 1 (1987), S. 243-245 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 1 (1987), S. 221-230 
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    Keywords: Pattern recognition ; SIMCA ; PCA ; Classification ; Recall ; Cross-validation ; Indicator function ; Leave-x-out ; Pseudo random data sets ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: The SIMCA pattern recognition method has been evaluated with pseudo random data sets. The number of objects varied from 5 to 50 and the number of features from 5 to 300.First, the determination of the significant number of PCs in the SIMCA models by the cross-validation method was compared with the indicator function. The results showed that for the lower dimensions (≤ 15 objects or ≤ 15 features) the indicator function produces more reliable results.Second, the classification results with SIMCA were analysed for data sets with two equally sized classes and a varying number of objects and features, using the recall function as the evaluation criterion. The results showed that the SIMCA classifier produces reliable results at the first classification level, even for a low object/feature ratio (5/300). However, at the second level the classification performance of SIMCA decreases rapidly with an increasing number of features, even when the data set consists of two very well separated classes and little random error.
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    Keywords: Pattern recognition ; SIMCA ; PCA ; Classification ; Bacteria ; Pyrolysis mass spectra ; Recall ; Cross-validation ; Indicator function ; Pseudo random data sets ; Leave-x-out ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: As part of a critical evaluation of the pattern recognition method SIMCA, three data sets containing pyrolysis mass spectra from bacteria were analysed using the SIMCA classifier. Each set consisted of two classes, Pseudomonas and Serratia bacteria, each class containing ten mass spectra and each mass spectrum having 285 spectral features.The results indicate that for these py-MS data sets, with low object/feature ratio, the SIMCA classifier produces satisfactory results at the first classification level. At the second level, however, the classification results are not reliable, even after deleting outliers. A comparison of the cross-validation method and Malinowski's indicator function for the determination of the number of significant principal components showed that the cross-validation method is less stable and therefore less reliable than the indicator function.
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    Journal of Chemometrics 1 (1987), S. 246-247 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Topics: Chemistry and Pharmacology
    Notes: STATA: VERSION 1.5, available from Computing Resources Center, 10801 National Boulevard, Los Angeles, CA 90064, U.S.A. Telex: 263199 STATAPC. Published by the Computing Resources Center, 1986. Basic version, for data management, data presentation, statistical testing, estimation, including linear regression, ANOVA and ANCOVA, with two program collections (written in the STATA programming language ) for (1) parametric and non-parametric tests and (2) generation of statistical graphs. Price: $395 in North America, $470 elsewhere (academic discount price in North America: $265).STATE GRAPHICS MODULE, for high-resolution statistical graphics, including one-way and two-way scatter plots, scatter-plot matrices, box plots, bar and pie charts, multiple imaging and overlays. Price: $195 in North America, $270 elsewhere (academic discount price in North America: $130).
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    Journal of Chemometrics 1 (1987), S. 248-249 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 2 (1988), S. 81-84 
    ISSN: 0886-9383
    Keywords: Multiclass analysis ; Covariance correlation display ; Variable Discriminant plots ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Principal component analysis is a useful method for analysing data-matrices. By analysing separate class models, i.e. disjoint principal component modelling as in the SIMCA or FCVPC programs (developed for supervised and unsupervised principal component analysis respectively), the principal component variance/covariance decomposition (class models) may be used to investigate and interpret the data-structure of separate classes. The potential of comparing the loadings of variables on subsequent eigenvectors in two class models where the same variables have been used will give information for determining how the variance/covariance in the two datasets differ. This information may then be used either to formulate a hypothesis or to select variables which are specific for the different classes.
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    Journal of Chemometrics 2 (1988), S. 91-92 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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  • 85
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    Journal of Chemometrics 2 (1988), S. 85-89 
    ISSN: 0886-9383
    Keywords: Linear discriminant functions ; Pattern recognition ; Monte Carlo simulations ; Chance classification ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Classification rules using non-parametric linear discriminant functions are often developed from training sets that are not linearly separable. In these situations it is a common practice among inexperienced workers to use many different pattern recognition methods and then select the results that look the best. However, this practice will only increase the risk of spurious results. To document this, we recently carried out a series of Monte Carlo simulation studies to assess the level of chance classification for two different classification algorithms. The level of chance classification for a given dichotomy is found to vary with the choice of the non-parametric linear discriminant function employed. Although previous workers have indicated that the degree of separation in the data due to chance is only a function of the object-to-descriptor ratio, the results of this study suggest otherwise.
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  • 86
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    Journal of Chemometrics 2 (1988) 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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  • 87
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    Journal of Chemometrics 2 (1988), S. i 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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  • 88
    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).
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  • 89
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    Journal of Chemometrics 2 (1988), S. 155-167 
    ISSN: 0886-9383
    Keywords: Principal component regression ; Multivariate calibration ; Near-infrared reflectance ; Prediction ability ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: In this paper we present formulae for prediction error related to principal component regression (PCR). The difference between PCR and ordinary least-squares (LS) regression is discussed in relation to these formulae. This discussion is used as a basis for a treatment of PCR in NIR analysis. The theory is illustrated by two examples from NIR analysis.
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  • 90
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    Journal of Chemometrics 2 (1988), S. i 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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  • 91
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    Journal of Chemometrics 2 (1988), S. 189-202 
    ISSN: 0886-9383
    Keywords: Computing system performance evaluation ; Ion microscopic analysis ; Digital image processing ; Monte Carlo simulations ; Supercomputer ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: There has been a steadily increasing demand for more computational power in surface and interface analysis. This paper reports attempts to meet these demands through the use of different computing systems, ranging from minicomputer to supercomputer. Representative laboratory data processing programs for ion microscopic analysis are used to evaluate the performance of each system. The bottlenecks and other problems involved in running analytical programs on faster machines are identified and discussed. Results indicate that in order to attain the optimal cost-performance ratio, programs must be tailored to specific forms required by the computing system. Algorithms must be formulated to exploit available vector and parallel processing capabilities.
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  • 92
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    Journal of Chemometrics 2 (1988), S. 121-136 
    ISSN: 0886-9383
    Keywords: Discriminant analysis ; Linear mixtures ; Residual vectors ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: In an earlier paper by Burdick and Rayens a model was developed which uses discriminant analysis to construct estimates of linear mixing proportions. In this paper a method is proposed for identifying potentially unreliable estimates when using the Burdick/Rayens model. It is also shown to be useful in detecting irregularities in the sample data. The methodology is based on the lengths of residual vectors and is demonstrated within the context of polychlorinated biphenyl mixtures.
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  • 93
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    Journal of Chemometrics 2 (1988), S. 137-154 
    ISSN: 0886-9383
    Keywords: Recursive parameter estimation ; Digital filtering ; Kinetic analysis ; Kalman filtering ; Computational efficiency ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: The extended Kalman filter has been used to estimate initial reactant concentrations and rate constants for rate-based chemical assays employing a second-order chemical reaction. Application of first- and second-order models to data permits reaction order identification by examining either the filter innovations or the evolution of the filter states. Because of non-linearities in the second-order kinetic model, repetitive filtering is necessary for convergence to reliable state estimates. Reduction of the filter calculation burden is investigated through the use of information-based filter methods, and it is demonstrated that substantial decreases in the computational burden are possible without loss of filter accuracy. These decreases make possible the application of second-order filters on large data sets, and they make real-time filtering possible with a fast processor.
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  • 94
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    Journal of Chemometrics 3 (1989), S. 547-547 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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  • 95
    ISSN: 0886-9383
    Keywords: Evolving factor 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: Evolving factor analysis is used to estimate the concentration profiles and spectra of Bi3+ and the bismuth chloride complexes BiC12+ through BiCl63- formed by injection of bismuth perchlorate into a flowing stream of 1·0 mol 1-1 HCl. The estimated spectra compare favorably with previously published spectra of the complexes.
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  • 96
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    Journal of Chemometrics 3 (1989), S. 463-475 
    ISSN: 0886-9383
    Keywords: Classification ; Discriminant analysis ; Principal components ; Biased estimates ; Cross-validation ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Classification and regression techniques are among the most used tools by chemometricians. With classification, the two classic methods are discriminant analysis and SIMCA. In this paper we discuss the connection between these two methods and introduce two new ones of the same family: DASCO (discriminant analysis with shrunken covariances) and RDA (regularized discriminant analysis). We demonstrate on both simulated and real data sets that their performance is superior to the old favorites. This is especially true in small-sample/high-dimension settings typical in chemistry.
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  • 97
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    Journal of Chemometrics 3 (1989), S. 493-498 
    ISSN: 0886-9383
    Keywords: Rank annihilation ; Generalized rank annihilation method ; Generalized eigenproblem ; Calibration ; Spectral interferents ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: An improved algorithm for the generalized rank annihilation method (GRAM) is presented. GRAM is a method for multicomponent calibration using two-dimensional instruments, such as GC-MS. In this paper an orthonormal base is first computed and used to project the calibration and unknown sample response matrices into a lower-dimensional subspace. The resulting generalized eigenproblem is then solved using the QZ algorithm. The result of these improvements is that GRAM is computationally more stable, particularly in the case where the calibration sample contains chemical constituents not present in the unknown sample and the unknown contains constituents not present in the calibration (the most general case).
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  • 98
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    Journal of Chemometrics 3 (1989), S. 477-491 
    ISSN: 0886-9383
    Keywords: Principal components analysis ; Cross-validation ; Procrustes rotation ; Variable selection ; Quality control ; Aviation turbine fuel ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Given a set of test criteria that determine a quality specification, the question often arises whether any of the tests are redundant because of intercorrelations Simple selection of tests on the basis of partial correlations with the other tests is rejected on the basis that the random error in the data may be causing spurious correlations.One method is to use cross-validation to define the systematic principal components and examine the correlation structure in this reduced space. It is shown that the presence of principal components dominated by individual tests (‘variable specific’ PCs), which are indicated by cross-validation as being non-systematic, must be taken into account. Having defined the dimensionality, a variable reduction method based on Procrustes rotation selects subsets of tests that preserve the structure of the samples in multivariate space. This is an attractive proposition in the context of maintaining a quality control specification. It is also shown that the variable reduction technique can be used to aid the identification of the true dimensionality of the data space. This approach is applied to a number of routine tests carried out on aviation turbine fuel.
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  • 99
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    Journal of Chemometrics 3 (1989), S. 499-509 
    ISSN: 0886-9383
    Keywords: Optimization ; Response surface ; PLS ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: The paper presents a procedure to obtain response surfaces with non-designed data. The method is based on PLS modelling of the expanded X-matrix followed by transformation of the PLS loadings into polynomial coefficients and detection of the co-ordinates of the best response within the experimental domain. The results are presented both graphically and numerically. The procedure is validated on an optimization study of the yield of an organic reaction.
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  • 100
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    Journal of Chemometrics 9 (1995), S. 137-138 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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