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  • Analytical Chemistry and Spectroscopy  (18)
  • Multivariate  (3)
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  • 1
    Electronic Resource
    Electronic Resource
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 7 (1993), S. 439-445 
    ISSN: 0886-9383
    Keywords: Calibration ; Rank annihilation ; Residual bilinearization ; Three-way ; Trilinear ; Net analyte rank ; Second-order ; Generalized rank annihilation method (GRAM) ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Through theoretical analysis and computer simulation, this short communication comments on the residual bilinearization (RBL) method and compares it with non-bilinear rank annihilation (NBRA) for the treatment of second-order calibration with non-bilinear data. It is found that these two methods are mathematically equivalent but have different noise propagation properties. The second-order advantage, namely quantitation in the presence of unknown interferences, can be carried over to non-bilinear data only if there exists a net analyte rank (NAR) for the analyte of interest.
    Additional Material: 1 Ill.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    New York, NY : Wiley-Blackwell
    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.
    Additional Material: 2 Ill.
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    New York, NY : Wiley-Blackwell
    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.
    Additional Material: 7 Tab.
    Type of Medium: Electronic Resource
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  • 4
    Electronic Resource
    Electronic Resource
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 1 (1987), S. 19-31 
    ISSN: 0886-9383
    Keywords: Calibration ; Indirect calibration ; Multivariate ; Matrix decomposition ; PLS ; PCR ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Partial least squares (PLS) modeling is an algorithm for relating one or more dependent variables to two or more independent variables. As a regression procedure it apparently evolved from the method of principal components regression (PCR) using the NIPALS algorithm, which is similar to the power method for determining the eigenvectors and eigenvalues of a matrix. This paper presents a theoretical explanation of the PLS algorithm using singular value decomposition and the power method. The relation of PLS to PCR is demonstrated, and PLS is shown to be one of a continuum of possible solutions of a similar type. These other solutions may give better prediction than either PLS or PCR under appropriate conditions.
    Additional Material: 4 Tab.
    Type of Medium: Electronic Resource
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  • 5
    Electronic Resource
    Electronic Resource
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 2 (1988), S. 67-79 
    ISSN: 0886-9383
    Keywords: Experimental design ; Multivariate calibration ; Variable selection ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Methods of multivariate calibration use models that relate spectral data or sensor array responses to the concentrations of analytes. The goal is to insure that the calibration model can accurately estimate analyte concentrations in unknown samples not contained in the calibration set. The sensors or spectral channels (e.g. wavelengths) selected for incorporation in the model, as well as the samples selected for the calibration step, are known to have an effect on the accuracy of analysis for unknown samples. This work provides a fundamental treatment of this effect and derives criteria for optimal selection. Additionally, a proof is given for the advantage of having more sensors and calibration samples than analytes - the overdetermined case.
    Additional Material: 5 Ill.
    Type of Medium: Electronic Resource
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  • 6
    Electronic Resource
    Electronic Resource
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 2 (1988), S. 93-109 
    ISSN: 0886-9383
    Keywords: Multivariate calibration ; Error estimation ; Confidence intervals ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: When arrays of non-selective sensors or overlapping spectra are used for chemical analysis, multivariate calibration must be used to relate the instrument responses to individual analytes. Using a set of carefully selected calibration samples, a multivariate mathematical model is constructed for one or more analytes. If this step is successful, the model can be used to predict the concentrations of these analytes in prospective samples. Previously, the equations required to estimate the errors in the predicted concentrations, and from these the confidence intervals, were not available because the three sources of error (measured responses from calibration data, concentrations of the analytes in the calibration set and measured responses from the unknown sample) propagated in a non-linear manner not amenable to statistical analysis. A new theory for error propagation is developed. The theory developed herein does not require estimates of the actual three sources of errors mentioned above and therefore is easy to implement. Data from near-infrared reflectance spectrometry of wheat samples were used to test the equations derived from the theory. Complete agreement between the true prediction errors and those estimated from the theory is demonstrated.
    Additional Material: 5 Ill.
    Type of Medium: Electronic Resource
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  • 7
    Electronic Resource
    Electronic Resource
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 2 (1988), S. 247-263 
    ISSN: 0886-9383
    Keywords: Calibration ; Tensor ; Multivariate ; PCR ; MLR ; PLS ; Regression ; Multidimensional arrays ; Order ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Many analytical instruments now produce one-, two- or n-dimensional arrays of data that must be used for the analysis of samples. An integrated approach to linear calibration of such instruments is presented from a tensorial point of view. The data produced by these instruments are seen as the components of a first-, second- or nth-order tensor respectively. In this first paper, concepts of linear multivariate calibration are developed in the framework of first-order tensors, and it is shown that the problem of calibration is equivalent to finding the contravariant vector corresponding to the analyte being calibrated. A model of the subspace spanned by the variance in the calibration must be built to compute the contravarian vectors. It is shown that the only difference between methods such as least squares, principal components regression, latent root regression, ridge regression and partial least squres resides in the choice of the model.
    Additional Material: 9 Ill.
    Type of Medium: Electronic Resource
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  • 8
    Electronic Resource
    Electronic Resource
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 2 (1988), S. 265-280 
    ISSN: 0886-9383
    Keywords: Calibration ; Tensor ; Multivariate ; Order ; Regression ; Generalized rank annihilation ; GRAM ; Multi order ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Tensorial calibration provides a useful approach to calibration in general. For calibration of instruments that produce two-dimensional (second-order) arrays of data per sample, tensoial concepts are as natural a way of solving the calibration problem as vectorial concepts are for the multivariate problem. Similarly, for third- and higher-order data, the tensorial description of calibration is also useful. This paper introduces second-order calibration from a tensorial point of view. Univariate, multivariate and bilinear approaches to calibration are presented. The generalized rank annihilation method (GRAM) is described from the tensorial perspective, and it is shown that GRAM is equivalent to finding a second-order tensorial base that spans both tensors (calibration and unknown) with respective diagonal component matrices. GRAM uses a single calibration sample for multicomponent analysis even in the presence of interference. Second-order bilinear calibration is extended to multiple calibration samples where the effect of collinearities is reduced.
    Additional Material: 5 Ill.
    Type of Medium: Electronic Resource
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  • 9
    Electronic Resource
    Electronic Resource
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 3 (1989), S. 493-498 
    ISSN: 0886-9383
    Keywords: Rank annihilation ; Generalized rank annihilation method ; Generalized eigenproblem ; Calibration ; Spectral interferents ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: An improved algorithm for the generalized rank annihilation method (GRAM) is presented. GRAM is a method for multicomponent calibration using two-dimensional instruments, such as GC-MS. In this paper an orthonormal base is first computed and used to project the calibration and unknown sample response matrices into a lower-dimensional subspace. The resulting generalized eigenproblem is then solved using the QZ algorithm. The result of these improvements is that GRAM is computationally more stable, particularly in the case where the calibration sample contains chemical constituents not present in the unknown sample and the unknown contains constituents not present in the calibration (the most general case).
    Type of Medium: Electronic Resource
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  • 10
    Electronic Resource
    Electronic Resource
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 6 (1992), S. 57-62 
    ISSN: 0886-9383
    Keywords: Closure ; Baseline ; Mean centering ; Rank ; Exploratory data analysis ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: This paper describes an investigation into the relationship of closure, a baseline offset and mean centering to the interpretation of matrix rank. The equivalence of a certain type of closure to a constant baseline (i.e. a simple numerical offset which may vary between response channels but is constant over all samples) is demonstrated. A systematic approach to the interpretation of the rank of a matrix is given.
    Additional Material: 4 Ill.
    Type of Medium: Electronic Resource
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