11-22
Approximation of the Fisher Information and Design in Nonlinear Mixed Effects Models
by Mielke, T.
Preprint series: 11-22, Preprints
- MSC:
- 62K05 Optimal designs
- 62J02 General nonlinear regression
Abstract: The missing closed form representation of the joint probability density of the observations is one main problem in the analysis of nonlinear mixed effects models. Often local approximations based on linearized models are then applied to approximately describe the properties of estimators. These local approximations are used for designing the experiments. The presentation of alternative motivations of Fisher information approximations are the aim of the present paper. Some locally optimal designs for a pharmacokinetic model are derived with the proposed approximations.
Keywords: Fisher information, mixed effects models, nonlinear models, optimal design
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