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A new method for the estimation of variance matrix with prescribed zeros in nonlinear mixed effects models |
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| Authors: | Djalil Chafaï Didier Concordet |
| Institution: | (1) UMR181, INRA, ENVT, 23, Chemin des Capelles, B.P. 87614, 31076 Toulouse CEDEX 3, France;(2) UMR CNRS 5219, Institut de Mathématiques de Toulouse, Université Paul Sabatier, 118 route de Narbonne, 31062 Toulouse CEDEX 9, France |
| Abstract: | We propose a new method for the Maximum Likelihood Estimator (MLE) of nonlinear mixed effects models when the variance matrix of Gaussian random effects has a prescribed pattern of zeros (PPZ). The method consists of coupling the recently developed Iterative Conditional Fitting (ICF) algorithm with the Expectation Maximization (EM) algorithm. It provides positive definite estimates for any sample size, and does not rely on any structural assumption concerning the PPZ. It can be easily adapted to many versions of EM. |
| Keywords: | Nonlinear mixed effects models Maximum likelihood Expected maximisation algorithm Longitudinal data analysis Repeated measurements Iterated proportional fitting algorithm Gaussian graphical models Stochastic inverse problems Pharmacokinetic/pharmacodynamics analysis |
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