Comparison of nonparametric methods in nonlinear mixed effects models

DOI10.1016/j.csda.2008.08.021zbMath1452.62245OpenAlexW2015796016MaRDI QIDQ961167

C. M. Laffont, J. Antic, Djalil Chafaï, Didier Concordet

Publication date: 30 March 2010

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

Full work available at URL: https://doi.org/10.1016/j.csda.2008.08.021

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Nonparametric estimation (62G05)

Related Items (8)

Parametric inference for stochastic differential equations driven by a mixed fractional Brownian motion with random effects based on discrete observations ⋮ Maximum likelihood estimation for stochastic differential equations driven by a mixed fractional Brownian motion with random effects ⋮ Nonparametric estimation for stochastic differential equations with random effects ⋮ Non parametric estimation for fractional diffusion processes with random effects ⋮ Editorial: Computational statistics within clinical research ⋮ Nonlinear nonparametric mixed-effects models for unsupervised classification ⋮ Nonparametric estimation for stochastic differential equations driven by mixed fractional Brownian motion with random effects ⋮ Nonparametric estimation of random-effects densities in linear mixed-effects model

Uses Software

• S-PLUS
• NONMEM
• MEMSS

Cites Work

• Unnamed Item
• Semi-Nonparametric Maximum Likelihood Estimation
• Nonlinear random effects mixture models: maximum likelihood estimation via the EM algorithm
• The geometry of mixture likelihoods: A general theory
• Consistency of maximum likelihood estimators for certain nonparametric families, in particular: Mixtures
• Nonparametric EM algorithms for estimating prior distributions
• On nonparametric maximum likelihood for a class of stochastic inverse problems
• Large deviation probabilities for certain nonparametric maximum likelihood estimators
• Nonparametric Maximum Likelihood Estimation of a Mixing Distribution
• Asymptotic Statistics
• The nonlinear mixed effects model with a smooth random effects density
• Nonparametric estimation in nonlinear mixed effects models
• Mixed-Effects Models in S and S-PLUS
• A maximum likelihood estimation method for random coefficient regression models
• Convergence Rates of SNP Density Estimators
• Estimating Heterogeneity in Random Effects Models for Longitudinal Data

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