Approximate Methods for Maximum Likelihood Estimation of Multivariate Nonlinear Mixed-Effects Models

Approximate Methods for Maximum Likelihood Estimation of Multivariate Nonlinear Mixed-Effects Models

Multivariate nonlinear mixed-effects models (MNLMM) have received increasing use due to their flexibility for analyzing multi-outcome longitudinal data following possibly nonlinear profiles. This paper presents and compares five different iterative algorithms for maximum likelihood estimation of the...

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Bibliographic Details
Main Author: Wan-Lun Wang
Format: Article
Language:English
Published: MDPI AG 2015-07-01
Series:Entropy
Subjects:
importance sampling
Laplacian approximation
Monte Carlo EM
penalized nonlinear least squares
pseudo expectation conditional maximization
Online Access:http://www.mdpi.com/1099-4300/17/8/5353

Internet

http://www.mdpi.com/1099-4300/17/8/5353

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