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A TEST OF THREE FITTING CRITERIA FOR MULTIRESPONSE NON-LINEAR MODELING
作者姓名:RANDY J.PELL  BRUCE R.KOWALSKI
作者单位:Center for Process Analytical Chemistry University of Washington,Seattle,WA 98195,U.S.A.,Current address:Analytical Sciences Laboratory,The Dow Chemical Company,1897 Building,Midland,MI 48667,U.S.A.Author to whom correspondence should be addressed.
摘    要:This work evaluates objective functions for multiresponse non-linear modeling using computersimulations.Tests are performed under a variety of signal-to-noise ratios and noise variance-covariancestructures.The standard error of prediction for the model parameters,computed from 50 trials,is usedfor performance comparisons.The full rank and rank-deficient problems are considered.For the fullrank problem one model was investigated,a first-order two-step consecutive reaction model,and twoobjective functions were considered,the total sum of squares and the determinant criterion.Nodistinction could be made between the two objective functions for this model.For the rank-deficient case two models were investigated,a first-order two-step consecutive reactionas in the full rank case,and a pH titration model described by the Henderson-Hasselbalch equation.Three objective functions were investigated for the rank-deficient case,the total sum of squares,aweighted total sum of squares and the determinant criterion.The total sum of squares was found toperform poorly under all conditions tested compared to the weighted total sum of squares and thedeterminant criterion.The determinant criterion was found to perform much better than the other twocriteria when the data have a combination of a low signal-to-noise ratio and high variance-covariancenoise structure.


A TEST OF THREE FITTING CRITERIA FOR MULTIRESPONSE NON-LINEAR MODELING
RANDY J.PELL,BRUCE R.KOWALSKI.A TEST OF THREE FITTING CRITERIA FOR MULTIRESPONSE NON-LINEAR MODELING[J].Journal of Geographical Sciences,1991(4).
Authors:RANDY JPELL BRUCE RKOWALSKI Center for Process Analytical Chemistry  University of Washington  Seattle  WA  USA Current address:Analytical Sciences Laboratory  The Dow Chemical Company  Building  Midlan  MI  USA Author to whom correspondence should be addressed
Institution:RANDY J.PELL~ BRUCE R.KOWALSKI~ Center for Process Analytical Chemistry,University of Washington,Seattle,WA,U.S.A. ~ Current address:Analytical Sciences Laboratory,The Dow Chemical Company,Building,Midlan,MI,U.S.A.~ Author to whom correspondence should be addressed.
Abstract:This work evaluates objective functions for multiresponse non-linear modeling using computer simulations.Tests are performed under a variety of signal-to-noise ratios and noise variance-covariance structures.The standard error of prediction for the model parameters,computed from 50 trials,is used for performance comparisons.The full rank and rank-deficient problems are considered.For the full rank problem one model was investigated,a first-order two-step consecutive reaction model,and two objective functions were considered,the total sum of squares and the determinant criterion.No distinction could be made between the two objective functions for this model. For the rank-deficient case two models were investigated,a first-order two-step consecutive reaction as in the full rank case,and a pH titration model described by the Henderson-Hasselbalch equation. Three objective functions were investigated for the rank-deficient case,the total sum of squares,a weighted total sum of squares and the determinant criterion.The total sum of squares was found to perform poorly under all conditions tested compared to the weighted total sum of squares and the determinant criterion.The determinant criterion was found to perform much better than the other two criteria when the data have a combination of a low signal-to-noise ratio and high variance-covariance noise structure.
Keywords:Determinant criterion  Multiresponse non-linear fitting
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