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  • Analytical Chemistry and Spectroscopy  (25,033)
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  • 1
    Electronic Resource
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    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 5 (1991), S. 545-545 
    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
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    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 6 (1992) 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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  • 3
    ISSN: 0886-9383
    Keywords: Derivatization reaction ; Factorial design ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: A number of nucleophiles have been successfully identified and quantified using the Kröhnke reaction with 2,3-diphenyl derivatives of quinolizinium salts. Optimization of the reaction conditions by means of a mathematical model involving analysis of the response surface has led to a better understanding of the factors exerting an influence on the above reaction.The parameters chosen were temperature, reaction time, base concentration, water concentration and nucleophile concentration. The reaction was developed in polar aprotic solvents (acetone, acetonitrile). To facilitate the nucleophilic attack, the presence of an organic base (triethylamine) was necessary, although concentrations in excess of 0·15M did not alter the development of the reaction. Since pharmaceutical solutions are often aqueous, the influence of water on the reaction was studied. Low water volumes have no significant influence on the opening of the quinolizinium ring by the nucleophilic reagent. However, when the water proportion exceeded that of the organic solvent, the fluorescence intensity was lower than expected. Development of the fluorescent reaction product was first detected 5 min after the reaction started. The fluorescence intensity reached its optimum value after 138 min.
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  • 4
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    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 6 (1992), S. i 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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  • 5
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    Journal of Chemometrics 6 (1992), S. 65-83 
    ISSN: 0886-9383
    Keywords: Trilinear decomposition ; Receptor modeling ; Source identification ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: In many cases, monitoring data for ambient airborne particles can be organized in the form of a three-way data table with one way for chemical species, one for sampling periods and one for sites. A direct trilinear decomposition followed by a matrix reconstruction (DTDMR) is developed to analyze such a data table as a whole. The three-way data set is composed into three two-way matrices by a direct trilinear decomposition (DTD). The column vectors of each of the matrices are called ‘source profiles’, ‘emission patterns’ and ‘site coefficients’ respectively. Particulate sources are identified by examining both their source profiles and emission patterns. After the sources have been identified, emission patterns and site coefficients are used to produce a three-way matrix that gives estimates of mass contributions of sources to the samples collected at every site in every period. By simulation study, not only has the method been verified, but a good indicator has been found that shows the number of factors (i.e. sources) in the system. Unlike other receptor models, DTDMR does not require source profile data and does not involve trial-and-error procedures. Since DTDMR identifies sources based on variations in two dimensions, it has a higher potential to distinguish two sources that have similar chemical compositions. The DTDMR model has provided excellent results with simulated data and has been applied in a real world three-way data set.
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  • 6
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    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 6 (1992), S. 163-175 
    ISSN: 0886-9383
    Keywords: Multiple-correspondence analysis ; Starch granule description ; Image analysis ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Raw starch is composed botanically of characteristic granules of various sizes and shapes, so that each kind of starch may be characterized by the population of its granules. In the present study ten commercial starch species were studied: wheat, rice, manioc, potato, arrowroot, amylomaize, normal maize, waxy maize and two different banana species. Six variables measuring the size and shape of granules were obtained by image analysis. The objective was to find a method to describe and compare the granule populations of the ten species. For such a study, multiple-correspondence analysis (MCA) was applied. MCA makes it possible to draw similarity maps of categories and objects. For each starch species the frequency distributions (histograms) of the six variables were assessed and each granule was characterized by its species and the classes of histograms to which it belonged. MCA was applied to the granule table and a description of the histogram classes and the granules was obtained. From the variables description a general typology of the granules was deduced. The similarity maps showed considerable scatter of the granules for all species except rice. A particular species could therefore not be identified by a single granule, but the granule distribution seemed to be characteristic. MCA was an appropriate method to analyse these data because it points out non-linear relationships between quantitative and qualitative variables.
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  • 7
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    Journal of Chemometrics 6 (1992), S. 177-188 
    ISSN: 0886-9383
    Keywords: PLS ; Prediction error ; Background constituents ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: A modification of a technique proposed by Lorber and Kowalski for the estimation of prediction errors is presented. The method is applied to five data sets. The results show that for some data sets the estimated prediction errors are close to the actual prediction errors for samples within the calibration range, while samples outside the calibration range must be background corrected before quantification of the prediction error.
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  • 8
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    Journal of Chemometrics 6 (1992), S. 199-216 
    ISSN: 0886-9383
    Keywords: MARS ; Splines ; Multivariate calibration ; Non-linear ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: This tutorial paper presents a simplified view of one of the more recently published multivariate calibration methods particularly suited to dealing with non-linear data sets. The method is referred to as MARS and stands for multivariate adaptive regression splines. Simple examples are provided to explain the workings of the method.
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  • 9
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    Journal of Chemometrics 4 (1990), S. 47-50 
    ISSN: 0886-9383
    Keywords: Classification ; Pattern recognition ; Preprocessing ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Over the past 15 years the linear learning machine has been applied to a large number of chemical problems. The learning machine approach is conceptually simple and does not require knowledge about the statistical distribution of the data. However, there are problems associated with this approach. One problem which has not been investigated is the influence of mislabeled samples on the positioning of the hyperplane in feature space. If a few samples in a data set are incorrectly tagged prior to training (i.e. the samples are labeled as members of class 2 even though they are actually members of class 1), it is still possible using the linear learning machine to achieve a classification success rate of 100% for the training set. However, unfavorable results will be obtained for the prediction set. The magnitude of this effect and its potential implications regarding the proper use of the linear learning machine are discussed.
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  • 10
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    Journal of Chemometrics 4 (1990), S. 51-59 
    ISSN: 0886-9383
    Keywords: Deconvolution ; Jansson's method ; Peak restoration ; Iterative deconvolution ; Peak resolution ; Non-linear deconvolution ; Super-resolution ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: In previous papers Jansson's method was found to be successful at deconvolving severely overlapped gas chromatographic peaks. In the most recent paper the method was evaluated with respect to quantitative accuracy, peak area and retention time repeatability. The problems associated with deconvolving noisy data and some alternatives which can improve the ability of Jansson's method to deconvolve noisy data are discussed. These alternatives include presmoothing the data with a nine-point, third-order polynomial filter and data reblurring. This paper will test these methods on peaks with various degrees of resolution and signal-to-noise ratios.
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  • 11
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    Journal of Chemometrics 4 (1990), S. 61-77 
    ISSN: 0886-9383
    Keywords: Infrared ; Spectroscopy ; Spectrometry ; Retrieval ; Confirmation ; Chemometrics ; Adequate peaks ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: In the series of analytical techniques for identification of chemical substances, infrared spectrometry presents by far the highest information content. However, the information is most complicated too. It concerns a multitude of band positions, band intensities and band shapes, which, moreover, can be disturbed by matrix and other effects. The high redundancy, however, allows conclusions to be made by a qualitative, subjective procedure.IR is often used to prove the equality between a sample and a reference material, e.g. in quality control of a production process. In forensic control, the question to be answered is mostly not to prove equality, but whether or not the presence of a compound in a sample, e.g. a drug, can be proved. Moreover, testing has to be performed according to objective rules.To fulfil these requirements, a new retrieval algorithm, the ‘Adequate Peaks Search’, is presented. It concerns representing the reference spectra by sets of adequate peak positions and the sample spectrum by a set of all peak positions, whereafter the cross-sections of the sample set and the reference sets are determined. The concept ‘adequate peak’ is defined and criteria have been formulated to evaluate the results into a positive (presence of the analyte is proved) or negative (presence is not proved) conclusion.The detection limit when the Adequate Peaks Search (APS) method was applied was four to seven times lower than that attained by a number of experts.
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  • 12
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    Journal of Chemometrics 4 (1990), S. 79-90 
    ISSN: 0886-9383
    Keywords: PLS ; Three-way matrices ; Calibration ; Residual bilinearization ; Background correction ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: When using hyphenated methods in analytical chemistry, the data obtained for each sample are given as a matrix. When a regression equation is set up between an unknown sample (a matrix) and a calibration set (a stack of matrices), the residual is a matrix R.The regression equation is usually solved by minimizing the sum of squares of R. If the sample contains some constituent not calibrated for, this approach is not valid. In this paper an algorithm is presented which partitions R into one matrix of low rank corresponding to the unknown constituents, and one random noise matrix to which the least squares restrictions are applied. Properties and possible applications of the algorithm are also discussed.In Part 2 of this work an example from HPLC with diode array detection is presented and the results are compared with generalized rank annihilation factor analysis (GRAFA).
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  • 13
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    Journal of Chemometrics 4 (1990), S. 91-96 
    ISSN: 0886-9383
    Keywords: Sample size ; Monte Carlo ; Multivariate, normal ; Q-Q plots ; Classification ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Because many pattern recognition techniques are predicated on the assumption of mutivariate normal data, Monte Carlo simulation studies were performed to determine the number of samples that are necessary to describe a multivariate normal population adequately. From these studies we have learned that hundreds of samples are required. These results suggest that parametric procedures should only be used to analyze very large data sets.
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  • 14
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    Journal of Chemometrics 4 (1990), S. 97-100 
    ISSN: 0886-9383
    Keywords: Matrix decomposition ; NIPALS ; Principal component ; SIMCA ; PLS ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: The Non-linear Iterative Partial Least Squares (NIPALS) algorithm is used in principal component analysis to decompose a data matrix into score vectors and eigenvectors (loading vectors) plus a residual matrix. NIPALS starts with some guessed starting vector. The principal components obtained by NIPALS depends on the starting vector; the first principal component could not always be computed. Wold has suggested a starting vector for NIPALS, but we have found that even if this starting vector is used, the first principal component cannot be obtained in all cases. The reason why such a situation occurs is explained by the power method. A simple modification of the original NIPALS procedure to avoid getting smaller eigenvalues is presented.
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  • 15
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    Journal of Chemometrics 4 (1990), S. 101-101 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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  • 16
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    Journal of Chemometrics 4 (1990), S. 102-102 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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  • 17
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    Journal of Chemometrics 4 (1990) 
    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 4 (1990), S. 102-102 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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  • 19
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    Journal of Chemometrics 4 (1990), 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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  • 20
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    Journal of Chemometrics 4 (1990), S. 103-121 
    ISSN: 0886-9383
    Keywords: Kalman filter ; Recursive digital filter ; Square-root filter ; Information filter ; Parameter estimation ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: The use of recursive filtering techniques for parameter estimation in a variety of areas is reviewed. In particular, the Kalman filter algorithm is described, along with several variations, including square-root, UDUT and information filters. The solution to parameter estimation problems is discussed for both linear and non-linear models. Applications described include calibration, curve resolution in spectroscopy, chromatography, electrochemistry, kinetic analysis and process monitoring.
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  • 21
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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  • 22
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    Journal of Chemometrics 7 (1993), S. 243-253 
    ISSN: 0886-9383
    Keywords: Orthogonal expansion ; Mapping ; Modelling ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: In this paper we discuss the orthogonal expansion of data matrices and its application to mapping and modelling. Two new methods, modified optimal discriminant plane (MODP) for mapping and order Gram-Schmidt orthogonalization (OGSO) for modelling, are proposed and examples are given.
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  • 23
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    Journal of Chemometrics 7 (1993) 
    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 7 (1993), S. 381-392 
    ISSN: 0886-9383
    Keywords: Factor analysis ; Kolmogorov-Smirnov test ; Non-parametric tests in factor analysis ; Non-parametric test for principal components ; Principal component analysis ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Each eigenvector of the dispersion matrix [X]T [X] was shown to be a partial predictor of the original data matrix [X], the sum of the predictions from the individual principal components being equal to the expectance of [X]. By comparing the distributions of the members of two neighbouring predicted matrices, [X̃]1…i and [X̃]1…i+1 (i.e. the sums of the first i and i + 1 individual predictions respectively), it was shown that they should be indistinguishable provided that i is equal to or greater than the effective rank of [X], and significantly different otherwise. This was confirmed by analysing the visible absorption spectra of methyl orange and methyl red solutions as well as the Raman spectra of Na2SO4 and MgSO4 solutions. On the grounds of these findings, a non-parametric goodness-of-fit test for assessing the effective rank of [X] was proposed which proved to be comparatively conservative and more robust than most currently used tests.
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  • 25
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    Journal of Chemometrics 7 (1993), S. 447-452 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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  • 26
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    Journal of Chemometrics 7 (1993), S. 477-494 
    ISSN: 0886-9383
    Keywords: Three-way principal components analysis ; Core matrix ; Body diagonalization ; Lower and upper bounds ; Simulation ; Soil contamination ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: In contrast with conventional PCA, a direct superposition and joint interpretation of loading plots is not possible in three-way PCA, since there may be data variance which is described by unequal components of different modes. The contributions to variance of all possible combinations of components are described in the core matrix. Body diagonalization, which is achieved by appropriate rotation of component matrices, is an essential tool for simplifying the core matrix structure. The maximum degree of body diagonality which may be obtained from such transformations is analysed from both the mathematical and simulation viewpoints. It is shown that, at least in the average case, high degrees can be expected, which makes the procedure reasonable for many practical applications. Furthermore, simulation as well as theoretical derivation show that the success of body diagonality depends on the so-called polarity of the core array. The methodology is illustrated by a three-way data example from environmental chemistry.
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  • 27
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    Journal of Chemometrics 7 (1993) 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
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  • 28
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    Journal of Chemometrics 7 (1993), S. 495-526 
    ISSN: 0886-9383
    Keywords: Standard errors ; Eigenvalues ; PCA ; MLR ; GRAM ; Rank estimation ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: New expressions are derived for the standard errors in the eigenvalues of a cross-product matrix by the method of error propagation. Cross-product matrices frequently arise in multivariate data analysis, especially in principal component analysis (PCA). The derived standard errors account for the variability in the data as a result of measurement noise and are therefore essentially different from the standard errors developed in multivariate statistics. Those standard errors were derived in order to account for the finite number of observations on a fixed number of variables, the so-called sampling error. They can be used for making inferences about the population eigenvalues. Making inferences about the population eigenvalues is often not the purposes of PCA in physical sciences. This is particularly true if the measurements are performed on an analytical instrument that produces two-dimensional arrays for one chemical sample: the rows and columns of such a data matrix cannot be identified with observations on variables at all. However, PCA can still be used as a general data reduction technique, but now the effect of measurement noise on the standard errors in the eigenvalues has to be considered. The consequences for significance testing of the eigenvalues as well as the usefulness for error estimates for scores and loadings of PCA, multiple linear regression (MLR) and the generalized rank annihilation method (GRAM) are discussed. The adequacy of the derived expressions is tested by Monte Carlo simulations.
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  • 29
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    Journal of Chemometrics 7 (1993), S. 559-566 
    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 8 (1994), S. 21-36 
    ISSN: 0886-9383
    Keywords: GRAM ; Tucker ; Unfold ; NBRA ; Second-order ; Three-way ; PARAFAC ; Trilinear ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: If an analytical instrument or instrumental method gives a response matrix when analyzing a pure analyte, the instrument or instrumental method is called a second-order method. Second-order methods that generate a response matrix for a pure analyte of rank one are called rank-one second-order methods. If the response matrix of a pure analyte is not rank one, essentially two cases exist: medium rank (between two and five) and high rank (greater than five). Subsequently, medium- and high-rank second-order calibration tries to use medium- and high-rank second-order methods to analyze for analytes of interest in a mixture. A particular advantage of second-order methods is the ability to analyze for analytes of interest in a mixture which contains unknown interferences. Keeping this advantage is the challenge on moving away from rank-one second-order calibration methods. In this paper a medium-rank second-order calibration method is proposed based on least-squares restricted Tucker models. With this method the second-order advantage is retained.
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  • 31
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    Journal of Chemometrics 8 (1994), S. 81-93 
    ISSN: 0886-9383
    Keywords: Sensory evaluation ; Cumulative ranks ; Assessor variation ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: A graphical method of assessing differences between sets of rankings based on cumulative ranks is developed. The method can be used to identify rankings that differ over all or just part of the range of objects ranked. The method is applied to an example of sensory evaluation of green peas in which ten assessors scored six attributes on each of 60 samples.
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  • 32
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    Journal of Chemometrics 8 (1994), S. i 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Topics: Chemistry and Pharmacology
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  • 33
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    Journal of Chemometrics 8 (1994), S. 155-168 
    ISSN: 0886-9383
    Keywords: Trilinear models ; Tensorial resolution ; PARAFAC ; Swamps ; Two-factor degeneracy ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: The alternating least squares PARAFAC algorithm is a useful tool for resolving trilinear three-way data arrays. Occasionally, however, it becomes bogged down for many iterations in the vicinity of a poor quality resolution before moving on to a much superior optimum fit. We investigate this behavior in a simulation study and suggest ways of overcoming the obstacles it presents.
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  • 34
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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  • 35
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    Journal of Chemometrics 8 (1994), S. i 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Topics: Chemistry and Pharmacology
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  • 36
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    Journal of Chemometrics 8 (1994), S. 181-203 
    ISSN: 0886-9383
    Keywords: RAFA ; GRAM ; Eigenvalues ; Bias ; Variance ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Rank annihilation factor analysis (RAFA) is a method for multicomponent calibration using two data matrices simultaneously, one for the unknown and one for the calibration sample. In its most general form, the generalized rank annihilation method (GRAM), an eigenvalue problem has to be solved. In this second paper expressions are derived for predicting the bias and variance in the eigenvalues of GRAM. These expressions are built on the analogies between a reformulation of the eigenvalue problem and the prediction equations of univariate and multivariate calibration. The error analysis will also be performed for Lorber's formulation of RAFA. It will be demonstrated that, depending on the size of the eigenvalue, large differences in performance must be expected. A bias correction technique is proposed that effectively eliminates the bias if the error in the bias estimate is not too large. The derived expressions are evaluated by Monte Carlo simulations. It is shown that the predictions are satisfactory up to the limit of detection. The results are not sensitive to an incorrect choice of the dimension of the factor space.
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    Journal of Chemometrics 4 (1990), S. i 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Topics: Chemistry and Pharmacology
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  • 38
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    Journal of Chemometrics 4 (1990), S. 337-354 
    ISSN: 0886-9383
    Keywords: Chemometrics ; Chemometrics Society ; History of chemometrics ; Pioneers of modern chemometrics ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: This is a first foray into the historical start and early years of chemometrics from about 1972 onwards. We have gathered interviews with three originators (Kowalski, Wold and Massart) as well as with a selected group of six other well-known chemometricians who gradually became active in the 1970s (Christie, Clementi, Hopke, Martens, Brown and Deming). The interviews include amongst a host of subjective recollections a succinct record of the key historical literature as highlighted by the interviewees' own rankings of ‘earliest’ and ‘best’.A discussion of the most general commonalities in these interviews together with other historical material is presented in the second part of the paper.
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  • 39
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    Journal of Chemometrics 4 (1990), S. 355-360 
    ISSN: 0886-9383
    Keywords: Pattern recognition ; U.K. chemometrics usage ; Quantitative structure-activity relationships ; Artificial intelligence ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: A survey of members of the U.K. QSAR Discussion Group has been made to determine the extent of use and development of chemometric and artificial intelligence (AI) methods in the analysis of multivariate quantitative structure-activity relationship (QSAR) data in the U.K. Chemometric methods were found to be well established in both industrial and educational establishments and there was significant method development occurring. AI methods were not employed to any great extent and the general level of interest in these techniques was low compared to chemometric methods. A requirement for more education in multivariate statistical methods and regression methods was indicated. A need for a user-friendly, comprehensive, commercially available multivariate statistical package containing multivariate stability testing and regression diagnostic methods was identified.
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    Journal of Chemometrics 4 (1990), S. 361-377 
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    Keywords: Abstract factor analysis ; Exploratory data analysis ; Principal components ; Simulated equilibria ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Abstract factor analyses were performed on databases consisting of simulated samples from aqueous equilbria. The program COMPLEX was used to generate equilibrium species in a system of three reactant metals and five reactant bases. Reactant concentrations and pH were drawn from random-normal distributions so that sample data vectors comprised a multivariate log-normal distribution of equilibrium concentrations. In addition, sample groups were created containing different distributions for pH and reactant concentrations.Equilibrium species were shown to contain variance contributed by change in pH among samples as well as change in reactant concentrations. Factor modelling revealed the qualitative relationships among the species and how the relationships change with pH. Factors also revealed those reactants containing variance in the data matrix. In some cases, reactant variance obscured relationships between pH and the equilibrium species.Since factor modelling of a simulated data matrix revealed the expected chemical equilibrium interactions, a potentially powerful tool exists for investigating the effects of outliers and error.
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  • 41
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    Journal of Chemometrics 8 (1994), S. 301-302 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Topics: Chemistry and Pharmacology
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    Journal of Chemometrics 8 (1994) 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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  • 43
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    Journal of Chemometrics 8 (1994), S. 305-331 
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    Keywords: Pyrolysis ; Mass spectroscopy ; Multivariate analysis ; Biological material identification ; Convexity ; Cones ; Subspaces ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: This work addresses the classification of high-dimensional time-dependent pyrolysis mass spectra of biological samples. The aim was the detection and classification of biological agents, and the developed approach resembles mixture analysis. The data were projected on to a low-dimensional subspace using singular value decomposition. Then a convex cone was formed on this subspace, showing as its corners physically meaningful components of the sample. This technique enabled separation of a biological material signal largely independent of the absolute amount of sample. The detection of the presence of any biological material could be accomplished based on the convex cone alone, without other reference to the mass spectra. Automated clustering of samples was successfully carried out using a minimal spanning tree.
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    Journal of Chemometrics 8 (1994), S. 373-373 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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  • 45
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    Journal of Chemometrics 4 (1990), S. 389-412 
    ISSN: 0886-9383
    Keywords: Chemometrics ; Chemometrics Society ; History of chemometrics ; Pioneers of modern chemometrics ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: This is a first foray into the historical start and early years of chemometrics from about 1972 onwards. We have gathered interviews with three originators (Kowalski, Wold and Massart) as well as with a selected group of six other well-known chemometricians who gradually became active in the 1970s (Christie, Clementi, Hopke, Martens, Brown and Deming). The interviews include amongst a host of subjective recollections a succinct record of the key historical literature as highlighted by the interviewees' own rankings of ‘earliest’ and ‘best’.A discussion of the most general commonalities in these interviews together with other historical material is presented in the second part of the paper.
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  • 46
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    Keywords: Discriminant analysis ; Size-exclusion chromatography ; Wheat proteins ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Continuous digitalized signals such as spectra, electrophoregrams or chromatograms generally have a large number of data points and contain redundant information. It is therefore troublesome performing discriminant analysis without any preliminary selection of variables. A procedure for the application of canonical discriminant analysis (CDA) on this kind of data is studied. CDA can be presented as a succession of two principal component analyses (PCAs). The first is performed directly on the raw data and gives PC scores. The second is applied on the gravity centres of each qualitative group assessed on the normalized PC scores. A stepwise procedure for selection of the relevant PC scores is presented. The method has been tested on an illustrative collection of 165 size-exclusion high-performance (SE-HPLC) chromatograms of proteins of wheat belonging to 55 genotypes and grown in three locations. The discrimination of the growing locations was performed using seven to nine PC scores and gave more than 86% accurate classifications of the samples both in the training sets and the verification sets. The genotypes were also rather well identified, with more than 85% of the samples correctly classified. The studied method gives a way of assessing relevant mathematical distances between digitalized signals according to qualitative knowledge of the samples.
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  • 47
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    Keywords: Principal components ; Multiple and stepwise regression ; Non-parametric density and regression estimation ; Bootstrap inference ; Canonical correlation ; PLS regression ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: A statistical study of the dependence between various critical fusion temperatures of a certain kind of coal and its chemical components is carried out. As well as using classical dependence techniques (multiple, stepwise and PLS regression, principal components, canonical correlation, etc.) together with the corresponding inference on the parameters of interest, non-parametric regression and bootstrap inference are also performed.
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  • 48
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    Journal of Chemometrics 9 (1995), S. 197-209 
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    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.
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    Journal of Chemometrics 5 (1991), S. 129-145 
    ISSN: 0886-9383
    Keywords: Multivariate calibration ; Biased regression ; Partial least squares (PLS) ; Principal component regression (PCR) ; Model validation ; Non-linear calibration ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: With the goal of understanding global chemical processes, environmental chemists have some of the most complex sample analysis problems. Multivariate calibration is a tool that can be applied successfully in many situations where traditional univariate analyses cannot. The purpose of this paper is to review multivariate calibration, with an emphasis being placed on the developments in recent years. The inverse and classical models are discussed briefly, with the main emphasis on the biased calibration methods. Principal component regression (PCR) and partial least squares (PLS) are discussed, along with methods for quantitative and qualitative validation of the calibration models. Non-linear PCR, non-linear PLS and locally weighted regression are presented as calibration methods for non-linear data. Finally, calibration techniques using a matrix of data per sample (second-order calibration) are discussed briefly.
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    Journal of Chemometrics 5 (1991), S. 147-161 
    ISSN: 0886-9383
    Keywords: Digital filtering ; Real-time analysis ; Kalman filtering ; Infrared spectroscopy ; Principal components regression ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Real-time monitoring of pollutant levels from a mobile measuring platform requires fast, flexible data analysis methods. This paper reports a method for rapid analysis of passive remotely sensed infrared data with the aid of a Kalman filter. The background spectra produced by emission from the atmosphere are modelled at the start of the data collection sequence with a simple principal components model obtained by eigenanalysis of the initial ‘blank’ data taken with the spectrometer. The species of interest are included in the state space model by a separate measurement of their infrared spectra. It is demonstrated that for best filter performance in detecting the simulated pollutant species SF6 in the atmosphere, a filter model with two principal components describing the emission background works best. The filter ‘maps’ of SF6 closely follow the integrated spectral intensities measured after removal of suitable backgrounds.
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    Journal of Chemometrics 5 (1991), S. 163-179 
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    Keywords: Principal component analysis ; Factor analysis ; Chemometrics ; Exploratory data analysis ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Principal component analysis is used to examine large multivariate databases. The graphical approach to exploratory data analysis is described and illustrated with a single example of chemical composition data obtained on environmental dust particles. While the graphical approach to exploratory data analysis has certain advantages over the numerical procedures, the empirical approach described here should be viewed as complementary to the more robust treatments that statistical methodologies afford.
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    Journal of Chemometrics 5 (1991), S. 181-192 
    ISSN: 0886-9383
    Keywords: Chemometrics ; Systems theory ; Experimental design ; Multivariate analysis ; Measurement science ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Chemometrics is defined as the application of mathematical and statistical methods to chemical systems. Systems theory is seen to be useful for organizing and categorizing the inputs to and outputs from chemical systems. Advances in measurement science in the 1950s and 1960s, particularly in analytical chemistry, created a need for a multivariate approach to data analysis. Early chemometrics emphasized the use of structure-finding methods for existing data sets. In many instances, data sets can be obtained from designed experiments. Such data sets are more likely to contain the desired information and the data can usually be acquired at less cost. Renewed interest in statistical process control will provide many new, more robust data sets in the future.
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    Journal of Chemometrics 5 (1991), S. 193-199 
    ISSN: 0886-9383
    Keywords: Kalman filter ; Chemometrics ; 5-Br-PADAP ; Metallic ions ; Simultaneous spectrophotometric determination ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: This paper describes the simultaneous determination of cobalt, nickel, copper, zinc and cadmium by spectrophotometry and the Kalman filter method. Co(II), Ni(II), Cu(II), Zn(II) and Cd(II) react with 5-bromo-2-(2-pyridylazo)-5-diethylaminophenol (5-Br-PADAP) in the presence of cationic surfactant cetyl pyridinium bromide (CPB) to form five different coloured ternary complexes. The absorption curves of these complexes overlap severely in the scanning range 500-620 nm. The Kalman filter algorithm is successfully applied to resolve the overlapped absorption curves and therefore makes the simultaneous determination of these metallic ions possible without tedious pretreatment. The proposed method is applied to analyse the titled elements in synthetic samples and in environmental samples such as hair, fingernail and river water samples with satisfactory results.
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    Journal of Chemometrics 5 (1991), S. 201-209 
    ISSN: 0886-9383
    Keywords: Uncertainty ; Step function ; Additive model ; Transformation ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: An additive model is used to express the observed value of a sample characteristic as the sum of the true sample characteristic and a value of the data collection error, commonly known as experimental error. The data uncertainty of the experimental results (or of a survey data set) is defined as the expected squared error. The expected squarred error may change with the sample characteristic, e.g. the error moment could be concentration-dependent. The relationship between the error variance and the analyte concentration may not be very distinct. In such a case the data transformation to stabilize the error moments may not be appropriate. A step function is proposed as an alternative way to represent the second moment of the error. The data uncertainty is defined as the weighted average of the step values of the second raw moment of the error, using the appropriate proportions of the routine samples as weights. The data uncertainties associated with the different data collection stages were evaluated by using regional soil survey data.
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    Journal of Chemometrics 5 (1991), S. 211-225 
    ISSN: 0886-9383
    Keywords: Shot noise ; Expectation-maximization ; Regression ; Deconvolution ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: A simple algorithm for deconvolution and regression of shot-noise-limited data is illustrated in this paper. The algorithm is easily adapted to almost any model and converges to the global optimum. Multiple-component spectrum regression, spectrum deconvolution and smoothing examples are used to illustrate the algorithm. The algorithm and a method for determining uncertainties in the parameters based on the Fisher information matrix are given and illustrated with three examples. An experimental example of spectrograph grating order compensation of a diode array solar spectroradiometer is given to illustrate the use of this technique in environmental analysis. The major advantages of the EM algorithm are found to be its stability, simplicity, conservation of data magnitude and guaranteed convergence.
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    Journal of Chemometrics 9 (1995) 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Topics: Chemistry and Pharmacology
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    Journal of Chemometrics 9 (1995), S. 451-457 
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    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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    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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    Journal of Chemometrics 5 (1991), S. 291-298 
    ISSN: 0886-9383
    Keywords: Absorbance ratio ; Statistical confidence ; Quality control ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Ratio measurements are commonly used to address a variety of analytical problems in environmental, forensic and pharmaceutical laboratories. In absorbance ratioing techniques, analytical chemists rely on the spectral features of the analyte(s) of interest. The absorbances at two wavelengths are monitored and the ratio of these two absorbances is computed. This ratio is then used to confirm the identity of the analyte(s) of interest, the purity of a product of the overlap of chromatographic peaks. These decisions often have far-reaching consequences (e.g. the identification of the source, biogenic or petrogenic, of hydrocarbons in biological tissues or water). Given the cost and the liabilities associated with such decisions, it is unfortunate that these ratios are seldom reported with any statistical confidence. The purpose of this study is to delineate the parameters that affect absorbance ratio measurements. The models that can be used to estimate the statistical confidence in these measurements are derived and evaluated experimentally. The results show that these models can estimate the relative standard deviations in absorbance ratios accurately. They can also estimate the effect of signal-to-noise ratio and the choice of wavelengths on the precision of absorbance ratios.
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    Journal of Chemometrics 5 (1991), S. 299-308 
    ISSN: 0886-9383
    Keywords: Errors in variables ; Orthogonal regression ; Latent variables ; Acid rain ; Acidic deposition ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Techniques for testing for and estimating relative bias between two laboratories are developed and applied to a survey of the chemistry of streams in the United States. The design of the quality assurance program allows estimation of linear corrections for bias as well as testing of the hypothesis of linearity. Designs of this type are useful, but improvements are suggested.
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    Journal of Chemometrics 5 (1991), S. 309-319 
    ISSN: 0886-9383
    Keywords: Confidence intervals ; Products of normal random variables ; Risk/exposure modeling ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: In many environmental applications, such as exposure assessment and risk modelling, the desired estimate is a random variable computed as the product of three independently distributed random variables. These variables may not necessarily have the same mean and variance. The method for finding the 100(1 - α)% confidence interval for the mean of the product random variable has been proposed by some practitioners as the product of the 100(1 - α)% confidence interval of the three means. In this paper we show that the distribution of the product of three independent normal variables is not normal. We find the mean and variance of the product distribution. Further, we show that although the mean of the product is equal to the product of the means, the product of the three confidence intervals is not a good approximation of the confidence intervals for the mean of the product variable. The confidence interval of the mean of the product variable may be estimated by computer simulation. An algorithm for estimating the confidence interval for the mean of the product random variable is given. The program implementing this algorithm is given as an appendix.
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    Journal of Chemometrics 5 (1991), S. 321-331 
    ISSN: 0886-9383
    Keywords: Screening ; Ground-water quality ; Monitoring ; Volatile organic compounds (VOCs) ; Optimization ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: It is shown that the presence of 31-35 commonly measured volatile organic compounds (VOCs) in ground water can be detected with small error rates by using screening methods which analyze for a subset of such VOCs. A study of selected data sets indicates that analytical determinations of only from two to eight VOCs will suffice to detect 95% of all VOC hits. It is also shown that a serially optimal algorithm for selecting the VOCs for screening is very nearly as accurate as a globally optimal algorithm and much easier to implement. These conclusions are supported by empirical evidence from two drinking-water data sets and one hazardous waste site data set. Additional research areas are also outlined.
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    Journal of Chemometrics 5 (1991) 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 5 (1991), S. i 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 5 (1991), S. 333-343 
    ISSN: 0886-9383
    Keywords: Rank estimation ; Bootstrap resampling ; Canonical correlation ; Excitation-emission matrix ; Singular value decomposition ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Rank estimation by canonical correlation analysis in multivariate statistics has been proposed as an alternative approach for estimating the number of components in a multicomponent mixture. A methodological turning point of this new approach is that it focuses on the difference in structure rather than in magnitude in characterizing the difference between the signal and the noise. This structural difference is quantified through the analysis of canonical correlation, which is a well-established data reduction technique in multivariate statistics. Unfortunately, there is a price to be paid for having this structural difference: at least two replicate data matrices are needed to carry out the analysis.In this paper we continue to explore the potential and to extend the scope of the canonical correlation technique. In particular, we propose a bootstrap resampling method which makes it possible to perform the canonical correlation analysis on a single data matrix. Since a robust estimator is introduced to make inference about the rank, the procedure may be applied to a wide range of data without any restriction on the noise distribution. Results from real as well as simulated mixture samples indicate that when used in conjunction with this resampling method, canonical correlation analysis of a single data matrix is equally efficient as of replicate data matrices.
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    Journal of Chemometrics 5 (1991), S. 345-360 
    ISSN: 0886-9383
    Keywords: Three-way PCA ; Three-way PLS ; PARAFAC ; Trilinear ; Unfolding ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: For the calibration of chromatographic systems, different methods can be used. One class of methods utilizes three-way approaches. The calibration problem is stated in such a way that the decomposition of a three-way array can serve for the prediction of retention on new stationary phases.Two three-way approaches are presented: the Unfold-PCA and PARAFAC models. The theory of both methods is presented and the differences are highlighted, the main difference being that PARAFAC is a trilinear decomposition whereas Unfold-PCA is not. Both three-way methods are evaluated on a small data set consisting of retention measurements of eight solutes at six mobile phase compositions on six stationary phases. The differences in performance of the two models are minor.For calibration purposes, two variants of the methods are discussed: three-way PLS and an extension of PARAFAC. Again the theory and differences between the two methods are explained. The predictive performance of the two methods is compared using the same data set as earlier. The differences in predictive performance, however, are minor. Both methods are capable of predicting 98% of the variation in the test sets. Yet, there are other considerations when comparing methods than predictive performance, e.g. the quality of the predictions.
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  • 68
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    Journal of Chemometrics 5 (1991), S. 361-374 
    ISSN: 0886-9383
    Keywords: Closure ; Normalization ; Multivariate trimming ; Minimum distance ; Bootstrap ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Compositional data arise naturally in several branches of science, including chemistry, geology, biology, medicine, ecology and manufacturing design. In chemistry, these constrained data seem to occur typically when raw data are normalized or when output is obtained from a constrained estimation procedure, such as might be used in a source apportionment problem. It is important not only for chemists to be aware that the usual multivariate statistical techniques are not applicable to constrained data, but also to have access to appropriate techniques as they become available. The currently available methodology is due principally to Aitchison and is based on log-normal models. This paper suggests new parametric and non-parametric approaches to significantly improve the existing methodology. In the parametric setting, some recent work of Rayens and Srinivasan is extended and a practical regression model is proposed. In the development of the non-parametric approach, minimum distance methods coupled with multivariate bootstrap techniques are used to obtain point and region estimators.
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  • 69
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    Journal of Chemometrics 5 (1991), S. 375-387 
    ISSN: 0886-9383
    Keywords: Determinant criterion ; Multiresponse non-linear fitting ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: This work evaluates objective functions for multiresponse non-linear modeling using computer simulations. Tests are performed under a variety of signal-to-noise ratios and noise variance-covariance structures. The standard error of prediction for the model parameters, computed from 50 trials, is used for performance comparisons. The full rank and rank-deficient problems are considered. For the full rank problem one model was investigated, a first-order two-step consecutive reaction model, and two objective functions were considered, the total sum of squares and the determinant criterion. No distinction could be made between the two objective functions for this model.For the rank-deficient case two models were investigated, a first-order two-step consecutive reaction as in the full rank case, and a pH titration model described by the Henderson-Hasselbalch equation. Three objective functions were investigated for the rank-deficient case, the total sum of squares, a weighted total sum of squares and the determinant criterion. The total sum of squares was found to perform poorly under all conditions tested compared to the weighted total sum of squares and the determinant criterion. The determinant criterion was found to perform much better than the other two criteria when the data have a combination of a low signal-to-noise ratio and high variance-covariance noise structure.
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    Journal of Chemometrics 5 (1991), S. 405-409 
    ISSN: 0886-9383
    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Topics: Chemistry and Pharmacology
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    Journal of Chemometrics 5 (1991), S. 389-403 
    ISSN: 0886-9383
    Keywords: Acoustic emission ; Pattern recognition ; Feature selection ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Features used to characterize acoustic emission signals from chemical systems are evaluated with regard to their potential for pattern recognition. Eight chemical systems involving phase transitions, hydration, dissolution and effervescence are employed and treated as separate signal classes. These are compared pairwise and the discriminatory capabilities of about 50 features are investigated by computing Fisher weights. Time domain and frequency domain descriptors are examined. Correlations among the features evaluated are also reported. Recommended descriptors are the mean and median frequencies, frequency bandwidth, number of level crossings (0% and 25%), crest factor (time and frequency domains), half-life, kurtosis and normalized percentiles of the signal and its power spectrum. The effectiveness of the recommended descriptors is demonstrated through the separation of signal classes in two different systems (melting ice and an enzyme-catalyzed gas formation reaction) by principal components analysis.
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  • 72
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 5 (1991), S. 416-416 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 5 (1991) 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 5 (1991), S. i 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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  • 77
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    Journal of Chemometrics 5 (1991), S. 417-434 
    ISSN: 0886-9383
    Keywords: Factor analysis ; Power density distribution ; Chromatography ; Absorption spectroscopy ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Evaluation of the results of factor analysis of sets of spectroscopically detected chromatograms is carried out by examining the shapes of the abstract factors. This is done either by visual inspection or by analysis of the power density spectra produced from them. Owing to constraints imposed by the column function and the spectroscopic instrument function, the information content of the chromatograms necessarily occurs at low spatial frequencies. As a consequence, it appears as relatively broad features in the abstract chromatograms and as a peak in the low-frequency region of the corresponding power density plot. On the basis of examination of the power density distribution, a well-defined distinction is made between primary and secondary abstract factors. The major uncertainty encountered in determining the number of chemical components appears to arise from effects of contaminants in reagents.
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    Journal of Chemometrics 5 (1991), S. 435-453 
    ISSN: 0886-9383
    Keywords: Class-modelling methods ; Potential functions ; Pattern recognition ; Discriminant analysis ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: A probabilistic and distribution-free class-modelling technique is developed from potential function discriminant analysis. In the multidimensional space of variables the class boundary is built either by the sample percentile of the probability density estimated by means of potential functions, or by the estimate of the ‘equivalent’ determinant of the variance-covariance matrix. The equivalent determinant is that of a hypothetical multivariate normal distribution whose mean probability density was obtained by potential functions. The bases of this modelling rule are evaluated by means of Monte Carlo experiments. The results on four datasets are used to measure the performances of this method, which equal and sometimes exceed the performances of parametric class-modelling methods based on linear and quadratic discriminant analysis which were used for comparison.
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    Journal of Chemometrics 5 (1991), S. 455-465 
    ISSN: 0886-9383
    Keywords: Correspondence analysis ; Cluster analysis ; Optimization ; Eigenanalysis ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Carey et al. utilized principal components analysis (PCA) to analyze frequency shift data obtained from piezoelectric sensors formed by coating quartz crystals with 27 different GC stationary phases and tested using 14 analytes. The objective of the analysis was to determine an optimal reduced set of coatings for detection of the analytes. The results were correlated with those obtained from cluster analysis. In this paper the data are re-analyzed using correspondence analysis (CA). The advantage of using CA include a symmetric treatment of sensor coatings and analytes and better identification of the representation of the analytes in terms of the detection components. The results obtained by the conjunctive use of PCA, a varimax rotation and cluster analysis were obtained by CA.
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    Journal of Chemometrics 5 (1991), S. 467-486 
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    Keywords: Expert system ; Neural network ; Fuzzy entropy ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: A fuzzy multivariate rule-building expert system (FuRES) has been devised which also functions as a minimal neural network. This system builds rules from training sets of data that use feature transformation in their antecedents. The rules are constructed using the ID3 algorithm with a fuzzy expression of classification entropy. The rules are optimal with respect to fuzziness and can accommodate overlapped and underlapped clusters of data. The FuRES algorithm combines the benefits obtained from simulated annealing and gradient optimization, which provide robustness and efficiency respectively. FuRES classification trees support OR logic in their inference. The system automatically generates meaningful and consistent certainty factors during rule construction. Unlike other neural networks, FuRES uses local processing which furnishes qualitative information in the rule structure of its classification trees and variable loadings of the weight vectors.
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    Journal of Chemometrics 5 (1991) 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 5 (1991), S. i 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 5 (1991), S. 487-501 
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    Keywords: Calibration ; Locally linear models ; Discrimination ; Optimality ; Chemistry ; Analytical Chemistry and Spectroscopy
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    Topics: Chemistry and Pharmacology
    Notes: A calibration situation is considered where the calibration data are split into subsets with good linear relationship between y and x within each group. Different strategies for good prediction in this case are proposed. Modifications for collinear data are considered and a simple simulated data set is used for illustration.
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    Journal of Chemometrics 5 (1991), S. 503-521 
    ISSN: 0886-9383
    Keywords: Antagonism ; Bounded ordinal scale ; Herbicide interaction ; Inter block comparisons ; Non-parametric ; Chemistry ; Analytical Chemistry and Spectroscopy
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    Topics: Chemistry and Pharmacology
    Notes: Studies of interactions among bioactive compounds are often difficult to interpret unambiguously. A priori assumptions about the nature of such interactions can seriously distort analysis of the data. By applying a rank order analysis appropriate to the naturally ordinal scale of response to xenobiotic insult, several co-herbicides were successfully identified from among numerous candidates in an experiment involving multiple blocks, rates and species. Moreover, underlying herbicide interactions were substantiated and identified which were not apparent by more traditional parametric analysis.
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    Journal of Chemometrics 6 (1992), S. 247-255 
    ISSN: 0886-9383
    Keywords: Analysis of variance ; Assumptions ; Graphics ; Models ; Validation of model ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: The computer has made it possible to scrutinize data rapidly by means of graphics. This should be done prior to the application of any model to the data, since the model must be validated before using it as a means of analyzing the data. The procedure is illustrated in terms of two examples of real experimental data.
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    Journal of Chemometrics 6 (1992), S. 284-285 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 6 (1992), S. 307-334 
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    Keywords: Non-linear PLS ; Quadratic regression ; Non-linear models ; Chemistry ; Analytical Chemistry and Spectroscopy
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    Topics: Chemistry and Pharmacology
    Notes: We treat here an extension of linear PLS regression to include regression on quadratic PLS components. The quadratic regression can be viewed as a natural extention of linear PLS regression to quadratic PLS according to the H-principle of mathematical modelling. The numerical implementation is treated in detail. It is shown that this approach can be used for models with large numbers of variables. Some modelling strategies are discussed depending on the purpose of the modelling. Applications of this approach are treated.
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    Journal of Chemometrics 6 (1992), S. 357-357 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 7 (1993) 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 7 (1993), S. 61-73 
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    Keywords: Compression ; Multivariate analysis ; B-splines ; Maximum entropy ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: For efficient handling of very large data arrays, pretreatment by compression is mandatory. In the present paper B-spline methods are described as good candidates for such data array compression. The mathematical relation between the maximum entropy method for compression of data tables and the B-spline of zeroth degree is described together with the generalization of B-spline compression to nth-order data array tables in matrix and tensor algebra.
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  • 91
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    Keywords: Factor analysis ; Window factor analysis ; Multicomponent analysis ; Ultraviolet spectroscopy ; Cu(II) complexes ; Ethylenediaminetetraacetic acid ; EDTA ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Window factor analysis (WFA) is a self-modeling chemometric technique for obtaining the concentration profiles of components from evolutionary processes such as chromotography, titration and reaction kinetics. By specifying the ‘window’, i.e. the region along the evolutionary axis indigenous to a component, the concentration profile of the component can be obtained without recourse to any information concerning the other components. Mathematical expressions required to perform such computations are derived. The method is applied to the investigation of copper(II) complexation with ethylenediaminetetraacetate (EDTA) by recording and factor analyzing the ultraviolet spectra of aqueous solutions containing a fixed amount of the disodium salt of EDTA and varying amounts of CuCl2. Evidence for four different species of EDTA is obtained. Clues concerning the stoichiometry of the species are garnered from the concentration profiles.
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    Journal of Chemometrics 7 (1993), S. 131-142 
    ISSN: 0886-9383
    Keywords: Classification ; Discriminant analysis ; Class modeling ; Specification limits ; Cross-validation ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: There are many chemical products where product conformity is decided upon by qualitative human judgements of overall product quality. Nowadays, quantitative instrumentally determined quality parameters become available which are intended to replace such qualitative judgements by means of automatic decision rules using multivariate specification limits. Six classification methods to derive such limits are compared in terms of their power to predict corresponding human judgemets on overall color conformity of 17 dyestuffs based on historical quality data. Standard statistical classification methods turned out to be unacceptable for the routine generation of decision rules because of the frequent distinct suboptimality of their predictive power. Instead, a simple non-statistical classification method utilizing a priori knowledge about the underlying data structure yielded uniformly satisfactory decision rules.
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    Journal of Chemometrics 7 (1993), S. 153-163 
    ISSN: 0886-9383
    Keywords: Generalized inverse ; K-matrix analysis ; P-matrix analysis ; Least squares ; Principal component regression ; Partial least squares ; Continuum regression ; Beer's law ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: This paper consists of two distinct but related parts. In the first part a geometric theory of generalized inverses is presented and a methodology based on this theory is developed and applied to solve the K-matrix and P-matrix forms of Beer's law. It is shown that most currently accepted and practiced methods for solving these forms of Beer's law are just special cases of this geometric theory of generalized inverses. In addition, this geometric theory is used to explain why the current methods work and why they fail.In the second part a general methodology that includes as special cases least squares, principal component regression, partial least squares 1 and 2, continuum regression plus a variety of other described and undescribed methodologies is presented and then applied to solve the P-matrix formulation of Beer's law. This general methodology, like the first, is also geometric in nature and relies on an understanding of projections.The main emphasis of this paper is one of perspective, which, if understood, provides the proper foundation for answering the general but extremely hard and possibly unanswerable question “what is the best method?”.
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    Journal of Chemometrics 7 (1993), S. 195-212 
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    Keywords: Calibration ; Non-linearity ; Principal components ; Stein estimate ; Chemistry ; Analytical Chemistry and Spectroscopy
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    Topics: Chemistry and Pharmacology
    Notes: A new regression method for non-linear near-infrared spectroscopic data is proposed. The technique is based on a model which is linear in the principal components and simple functions (squares and products) of them. Added variable plots are used to determine which squares and products to incorporate into the model. The regression coefficients are estimated by a Stein estimate which shrinks towards the estimate determined by the first several principal components and the selected non-linear terms. The technique is not computationally intensive and is appropriate for routine predictions of chemical concentrations. The method is tested on three data sets and in all cases gives more accurate predictions than does linear principal components regression.
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    Journal of Chemometrics 7 (1993), S. 227-242 
    ISSN: 0886-9383
    Keywords: Non-linear mapping ; Graphical methods ; SAR ; SPR ; Quality of representation ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: From a review of the theoretical aspects of non-linear mapping and the different algorithms available in the literature, the methodological and practical problems linked to the use of this multivariate method in structure-activity and structure-property relationship studies are underlined. Useful tools for the graphical display of the outputs and the interpretation of the obtained clusters are presented. Statistical parameters estimating the quality of the graphical representation of each individual are also introduced. An example of application on a data matrix of 37 acaricides described by four physicochemical descriptors (π, F, R, MR) is presented.
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    Journal of Chemometrics 7 (1993), S. 291-304 
    ISSN: 0886-9383
    Keywords: Partial least squares ; Monte Carlo methods ; Cross validation ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Partial least squares (PLS) regression is a commonly used statistical technique for performing multivariate calibration, especially in situations where there are more variables than samples. Choosing the number of factors to include in a model is a decision that all users of PLS must make, but is complicated by the large number of empirical tests available. In most instances predictive ability is the most desired property of a PLS model and so interest has centred on making this choice based on an internal validation process. A popular approach is the calculation of a cross-validated r2 to gauge how much variance in the dependent variable can be explained from leave-one-out predictions. Using Monte Carlo simulations for different sizes of data set, the influence of chance effects on the cross-validation process is investigated. The results are presented as tables of critical values which are compared against the values of cross-validated r2 obtained from the user's own data set. This gives a formal test for predictive ability of a PLS model with a given number of dimensions.
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  • 97
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    Keywords: Reaction kinetics ; Initial rate ; Kinetic order ; Response surface modelling ; Canonical analysis ; Organic synthesis ; Optimization ; Reaction mechanisms ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: A method is presented by which it is possible to estimate the initial rate of chemical reactions when the experimental conditions are varied according to a response surface design. The method is intended as a complementary method for analysing data obtained from experiments in synthetic chemistry when the objective is to optimize the yield of the reaction.Data obtained by simulations have been used to develop the method. From the simulated reactions it is shown that sequential analysis of the chemical yield of the reaction makes it possible to estimate models which describe how the parameters of the response surface of the yield vary over time. The derivatives of these time functions of the response surface parameters can be used to define a rate function which describes how the variations in the experimental conditions influence the rate of the reaction.It is shown how such rate functions can be used to afford reasonable estimates of the initial rates of the reaction. The initial reaction rates thus estimated can be used to determine the kinetic order of the reactants and also to provide estimates of the activation energy of the reaction.A thorough discussion of how canonical analysis of the rate function may assist in the elucidation of reaction mechanisms is given.
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    Journal of Chemometrics 7 (1993), S. 427-438 
    ISSN: 0886-9383
    Keywords: Quality control ; Kerosene ; Variable reduction ; Cross-validation ; Variable selection ; Procrustes rotation ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: This paper deals with a typical question encountered in all industrial analytical laboratories: are all the tests performed in the laboratory to characterize the final product really necessary? In this work the cross-validation technique, Procrustes rotation techniques and statistical variable selection have been used to reduce the 26 initial British Petroleum and ASTM kerosene specification test to ten ‘essential’ ones. Statistical as well as chemical considerations were used to select the optimum subset of original variables to be retained from all the possible ones.
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    Journal of Chemometrics 7 (1993), S. 453-454 
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    Keywords: Chemistry ; Analytical Chemistry and Spectroscopy
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    Journal of Chemometrics 7 (1993), S. 527-541 
    ISSN: 0886-9383
    Keywords: Principal component analysis ; Projection pursuit ; Simulated annealing algorithm ; Robust statistics ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Principal component analysis (PCA) is a widely used technique in chemometrics. The classical PCA method is, unfortunately, non-robust, since the variance is adopted as the objective function. In this paper, projection pursuit (PP) is used to carry out PCA with a criterion which is more robust than the variance. In addition, the generalized simulated annealing (GSA) algorithm is introduced as an optimization procedure in the process of PP calculation to guarantee the global optimum. The results for simulated data sets show that PCA via PP is resistant to the deviation of the error distribution from the normal one. The method is especially recommended for use in cases with possible outlier(s) existing in the data.
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