Chemometrics in Environmental Chemistry - Statistical Methods
Herausgegeben:Einax, Jürgen;Mitarbeit:Barnard, T. E.; Booksh, K. S.; Brereton, R. G.; Coomans, D. H.; Deming, S. N.; Hayashi, Y.; Mallet, Y. L.; Matsuda, R.; Nocerino, J. M.; Olivero, R. A.; Singh, Ajay;
Chemometrics in Environmental Chemistry - Statistical Methods
Herausgegeben:Einax, Jürgen;Mitarbeit:Barnard, T. E.; Booksh, K. S.; Brereton, R. G.; Coomans, D. H.; Deming, S. N.; Hayashi, Y.; Mallet, Y. L.; Matsuda, R.; Nocerino, J. M.; Olivero, R. A.; Singh, Ajay;
Pattern recognition and other chemometrical techniques are important tools in interpreting environmental data. This volume presents authoritatively state-of-the-art procedures for measuring and handling environmental data. The chapters are written by leading experts.
Pattern recognition and other chemometrical techniques are important tools in interpreting environmental data. This volume presents authoritatively state-of-the-art procedures for measuring and handling environmental data. The chapters are written by leading experts.
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Inhaltsangabe
of Volume 2 G: Statistical Methods.- Environmental Sampling.- Topics of Chemometrics Today.- Experimental Design and Optimization.- Signal Processing and Correlation Techniques.- Information Theory of Signal Resolution - Precision of Measurements.- Robust and Non-parametric Methods in Multiple Regressions of Environmental Data.- Extension and Application of Univariate Figures of Merit to Multivariate Calibration.- Robust Procedures for the Identification of Multiple Outliers.- Pattern Analysis and Classification.
of Volume 2 G: Statistical Methods.- Environmental Sampling.- Topics of Chemometrics Today.- Experimental Design and Optimization.- Signal Processing and Correlation Techniques.- Information Theory of Signal Resolution - Precision of Measurements.- Robust and Non-parametric Methods in Multiple Regressions of Environmental Data.- Extension and Application of Univariate Figures of Merit to Multivariate Calibration.- Robust Procedures for the Identification of Multiple Outliers.- Pattern Analysis and Classification.
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