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- W2011041305 abstract "Karjalainen, E.J. and Karjalainen, U.P., 1992. Simultaneous analysis of multiple chromatographic runs and samples with alternating regression. Chemometrics and Intelligent Laboratory Systems, 14: 423–427. Most chromatographic analyses use single-dimensional signals. Typical examples are gas chromatographic (GC) instruments with a flame ionization detector and high-performance liquid chromatographic instruments with fixed-wavelength UV detectors. The data are analyzed with special devices — integrators — that estimate the areas under the chromatographic peaks. The integrators process the measured data one chromatogram at a time. The integrators do not use shape models for the peaks. Instead, they skim peaks or draw lines to the baseline to separate the different analytes. We propose a new approach to the analysis of chromatographic data. Synchronized chromatograms from one batch of samples are analyzed as an entity. Any method used for the decomposition of two-dimensional data can be used. Two-dimensional data are produced by hyphenated instruments such as GC—mass spectrometry. Most decomposition methods are based on factor analysis. Our method, alternating regression, operates directly in the space of spectra and elution profiles. Decomposition of batches of single-dimensional data produces estimates of elution profiles and ‘spectral lines’ proportional to concentration. Additionally, we obtain an estimate how well the model describes each chromatogram. In summary, we can analyze single-dimensional data by combining data from many samples into a single two-dimensional matrix." @default.
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- W2011041305 title "Simultaneous analysis of multiple chromatographic runs and samples with alternating regression" @default.
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- W2011041305 doi "https://doi.org/10.1016/0169-7439(92)80124-m" @default.
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