An Optimal Design Criterion for Within-Individual Covariance Matrices Discrimination and Parameter Estimation in Nonlinear Mixed Effects Models
Keyword(s):
In this paper, we consider the problem of nding optimal populationdesigns for within-individual covariance matrices discrimination andparameter estimation in nonlinear mixed eects models. A compound optimality criterion is provided, which combines an estimation criterion and a discrimination criterion. We used the D-optimality criterion for parameter estimation, which maximizes the determinant of the Fisher information matrix. For discrimination, we propose a generalization of the T-optimality criterion for xed-eects models. Equivalence theorems are provided for these criteria. We illustrated the application of compound criteria with an example in a pharmacokinetic experiment.
2003 ◽
Vol 13
(2)
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pp. 209-227
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2013 ◽
Vol 40
(2)
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pp. 252-265
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2008 ◽
Vol 25
(18)
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pp. 184007
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2014 ◽
Vol 912-914
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pp. 1663-1668
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