| RECENT DEVELOPMENTS IN MULTIVARIATE CALIBRATION |
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| 作者姓名： | B.R.KOWALSKI M.B.SEASHOLTZ Laboratory for Chemometrics BG- University of Washington Seattle WA U.S.A. |
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| 作者单位： | B.R.KOWALSKI M.B.SEASHOLTZ Laboratory for Chemometrics，BG-10，University of Washington，Seattle，WA 98195，U.S.A. |
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| 摘 要： | With the goal of understanding global chemical processes,environmental chemists have some of the mostcomplex sample analysis problems.Multivariate calibration is a tool that can be applied successfully inmany situations where traditional univariate analyses cannot.The purpose of this paper is to reviewmultivariate calibration,with an emphasis being placed on the developments in recent years.The inverseand 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 methodsfor quantitative and qualitative validation of the calibration models.Non-linear PCR,non-linear PLSand 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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RECENT DEVELOPMENTS IN MULTIVARIATE CALIBRATION |
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| B.R.KOWALSKI M.B.SEASHOLTZ Laboratory for Chemometrics,BG-,University of Washington,Seattle,WA,U.S.A..RECENT DEVELOPMENTS IN MULTIVARIATE CALIBRATION[J].Journal of Geographical Sciences,1991(3). |
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| Authors: | BRKOWALSKI MBSEASHOLTZ Laboratory for Chemometrics BG- University of Washington Seattle WA USA |
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| Abstract: | 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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| Keywords: | Multivariate calibration Biased regression Partial least squares(PLS) Principal component regression(PCR) Model validation Non-linear calibration |
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