A hierarchical Bayesian approach for parameter estimation in HIV models

H. T. Banks, Sarah Grove, Shuhua Hu, Yanyuan Ma

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

A hierarchical Bayesian approach is developed to estimate parameters at both the individual and the population levels in a HIV model, with the implementation carried out by Markov Chain Monte Carlo (MCMC) techniques. Sample numerical simulations and statistical results are provided to demonstrate the feasibility of this approach.

Original languageEnglish (US)
Pages (from-to)1803-1822
Number of pages20
JournalInverse Problems
Volume21
Issue number6
DOIs
StatePublished - Dec 1 2005

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Signal Processing
  • Mathematical Physics
  • Computer Science Applications
  • Applied Mathematics

Fingerprint Dive into the research topics of 'A hierarchical Bayesian approach for parameter estimation in HIV models'. Together they form a unique fingerprint.

Cite this