Parameter estimation of two-level nonlinear mixed effects models using first order conditional linearization and the EM algorithm

DOI10.1016/J.CSDA.2013.05.026zbMath1471.62067OpenAlexW2051563091MaRDI QIDQ1615190

Shouzheng Tang, Yuancai Lei, Liyong Fu, Ming-Liang Wang

Publication date: 2 November 2018

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

Full work available at URL: https://doi.org/10.1016/j.csda.2013.05.026

zbMATH Keywords

expectation-maximization algorithm\textit{Cunninghamia lanceolata}first order conditional expansionLindstrom and Bates algorithmsimulated datatwo-level nonlinear mixed effects models

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Point estimation (62F10) General nonlinear regression (62J02) Analysis of variance and covariance (ANOVA) (62J10)

Related Items (1)

Maximum likelihood estimation of nonlinear mixed-effects models with crossed random effects by combining first-order conditional linearization and sequential quadratic programming

Uses Software

• S-PLUS
• SAS
• MEMSS
• NLINMIX

Cites Work

• Unnamed Item
• Random-Effects Models for Longitudinal Data
• Maximum likelihood estimation in nonlinear mixed effects models
• Nonlinear random effects mixture models: maximum likelihood estimation via the EM algorithm
• On the convergence properties of the EM algorithm
• Two Taylor-series approximation methods for nonlinear mixed models
• Convergence of a stochastic approximation version of the EM algorithm
• Extension of the SAEM algorithm for nonlinear mixed models with 2 levels of random effects
• Monte Carlo Comparison of ANOVA, MIVQUE, REML, and ML Estimators of Variance Components
• Multivariate Multilevel Nonlinear Mixed Effects Models for Timber Yield Predictions
• Newton-Raphson and EM Algorithms for Linear Mixed-Effects Models for Repeated-Measures Data
• Laplace's approximation for nonlinear mixed models
• An EM Algorithm for Nonlinear Random Effects Models
• Mixed-Effects Models in S and S-PLUS
• Maximum Likelihood Computations with Repeated Measures: Application of the EM Algorithm
• Exact and Approximate Inferences for Nonlinear Mixed-Effects Models With Missing Covariates

This page was built for publication: Parameter estimation of two-level nonlinear mixed effects models using first order conditional linearization and the EM algorithm