| THE PERFORMANCE OF LEAST SQUARES AND ROBUST REGRESSION IN THE CALIBRATION OF ANALYTICAL METHODS UNDER NON-NORMAL NOISE DISTRIBUTIONS |
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| 作者姓名： | R.WOLTERS G.KATEMAN |
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| 作者单位： | Department of Analytical Chemistry University of Nijmegen. Toernooiveld NL-6525 ED Nijmegen The Netherlands，Department of Analytical Chemistry University of Nijmegen. Toernooiveld NL-6525 ED Nijmegen The Netherlands |
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| 摘 要： | By means of Monte Carlo simulations a comparison has been made between ordinary least squaresregression and robust regression. The robust regression procedure is based on the Huber estimate and iscomputed by means of the iteratively reweighted least squares algorithm. The performance of bothprocedures has been evaluated for estimation of the parameters of a calibration function and fordetermination of the concentration of unknown samples. The influence of the distributionalcharacteristics skewness and kurtosis has been studied, and the number of measurements used forconstructing the calibration curve has also been taken into account, Under certain conditions robustregression offers an advantage over least squares regression.
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THE PERFORMANCE OF LEAST SQUARES AND ROBUST REGRESSION IN THE CALIBRATION OF ANALYTICAL METHODS UNDER NON-NORMAL NOISE DISTRIBUTIONS |
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| R.WOLTERS,G.KATEMAN.THE PERFORMANCE OF LEAST SQUARES AND ROBUST REGRESSION IN THE CALIBRATION OF ANALYTICAL METHODS UNDER NON-NORMAL NOISE DISTRIBUTIONS[J].Journal of Geographical Sciences,1989(1). |
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| Authors: | R WOLTERS G KATEMAN |
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| Institution: | R. WOLTERS,G. KATEMAN,Department of Analytical Chemistry,University of Nijmegen,Toernooivel,NL- ED Nijmegen,The Netherlands |
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| Abstract: | By means of Monte Carlo simulations a comparison has been made between ordinary least squares regression and robust regression. The robust regression procedure is based on the Huber estimate and is computed by means of the iteratively reweighted least squares algorithm. The performance of both procedures has been evaluated for estimation of the parameters of a calibration function and for determination of the concentration of unknown samples. The influence of the distributional characteristics skewness and kurtosis has been studied, and the number of measurements used for constructing the calibration curve has also been taken into account, Under certain conditions robust regression offers an advantage over least squares regression. |
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| Keywords: | Calibration Robust regression Iteratively reweighted least squares M-estimator Monte Carlo simulations |
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