摘要: A historic introduction to chemometrics is presented. Notation and matrix operations are also Multivariate curve resolution described, including the use of principal components analysis determination number in a series mixture spectra. Both noniterative iterative approaches resolving out characteristics (spectra concentration profiles) outlined. Calibration covered, univariate calibration, multiple linear regression, partial least squares, model validation assessment. Exploratory data discusses as method for visualization cluster analysis. Supervised methods include ways developing assessing classification models, descriptions class discriminant analysis, K-nearest neighbor method. Finally, multivariate statistical process control introduced. Keywords: chemometrics; principal analysis; partial squares; multivariate resolution; pattern recognition
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