Year: 2014
Type: preprint
Abstract: We consider constructing model selection criteria for evaluating nonlinear mixed effects models via basis expansions. Mean functions and random functions in the mixed effects model are expressed by basis expansions, then they are estimated by the maximum likelihood method. In order to select numbers of basis we derive a Bayesian model selection criterion for evaluating nonlinear mixed effects models estimated by the maximum likelihood method. Simulation results shows the effectiveness of the mixed effects modeling.
Source: arXiv (Cornell University)
Author: Matsui, Hidetoshi
Institution: Kyushu University
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W1663455592