A simulated pseudo-maximum likelihood estimator for nonlinear mixed models.

DOI10.1016/S0167-9473(01)00052-4zbMath1132.62337WikidataQ128054774 ScholiaQ128054774MaRDI QIDQ1605373

Didier Concordet, Olivier G. Nunez

Publication date: 15 July 2002

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

zbMATH Keywords

ConsistencyAsymptotic normalityNonlinear mixed effects modelSimulation estimator

Mathematics Subject Classification ID

General nonlinear regression (62J02)

Related Items (8)

Further Developments of the Fisher Information Matrix in Nonlinear Mixed Effects Models with Evaluation in Population Pharmacokinetics ⋮ Pseudo-likelihood estimation for discretely observed multitype Bellman--Harris branching proc\-esses ⋮ Quasi- and pseudo-maximum likelihood estimators for discretely observed continuous-time Markov branching processes ⋮ A Stochastic Model to Analyze Clonal Data on Multi‐Type Cell Populations ⋮ Choice of units of analysis and modeling strategies in multilevel hierarchical models ⋮ Maximum likelihood estimation in nonlinear mixed effects models ⋮ Coupling a stochastic approximation version of EM with an MCMC procedure ⋮ Estimating the life-span of oligodendrocytes from clonal data on their development in cell culture

Uses Software

• NONMEM

Cites Work

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• Estimation of nonlinear random coefficent models
• Consistency in Nonlinear Econometric Models: A Generic Uniform Law of Large Numbers
• A Bayesian Approach to Nonlinear Random Effects Models
• A note on the use of Laplace's approximation for nonlinear mixed-effects models
• Consistent Estimators in Generalized Linear Mixed Models
• Bayesian Analysis of Linear and Non-Linear Population Models by Using the Gibbs Sampler

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