Monte Carlo likelihood estimation of mixed-effects state space models with application to HIV dynamics
type: Item
instance of: scholarly article
title: Monte Carlo likelihood estimation of mixed-effects state space models with application to HIV dynamics
zbMATH Open document ID: 1346.93372
author: Aiping Tang
author: Jie Zhou
author: Hai-Lin Feng
published in: Journal of Systems Science and Complexity
publication date: 2016-10-21T00:00:00Z
Mathematics Subject Classification ID: 93E10
Mathematics Subject Classification ID: 93E11
Mathematics Subject Classification ID: 93C55
zbMATH DE Number: 6641844
zbMATH Keywords: mixed-effects
zbMATH Keywords: mixture Kalman filter
zbMATH Keywords: state estimation
zbMATH Keywords: state space model
MaRDI profile type: Publication
full work available at URL: s11424-016-4158-9
OpenAlex ID: W2518253223
cites work: Mixed-Effects State-Space Models for Analysis of Longitudinal Dynamic Systems
cites work: Mixture Kalman Filters
cites work: Following a moving target -- Monte Carlo inference for dynamic Bayesian models
cites work: Q4864274
cites work: Q4272808
cites work: Q2753033
cites work: Q2753031
cites work: Hierarchical Bayesian Methods for Estimation of Parameters in a Longitudinal HIV Dynamic System
cites work: Time series analysis by state space methods.
DOI: 10.1007/S11424-016-4158-9
description: scientific article; zbMATH DE number 6641844