Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1151923 | Statistics & Probability Letters | 2013 | 9 Pages |
Abstract
Nonlinear state space models with mixed-effect (NLMESSM) are proposed to model HIV clinical longitudinal data. With NLMESSM, filtering algorithms are proposed to estimate the individual/population states. Maximum likelihood via iterated filtering and variance components model are proposed to estimate fixed/random effects respectively. Simulation results validate the effectiveness of NLMESSM.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Jie Zhou, Lu Han, Sanyang Liu,