Ontology highlight
ABSTRACT:
SUBMITTER: Touloupou P
PROVIDER: S-EPMC7455056 | biostudies-literature | 2020
REPOSITORIES: biostudies-literature
Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America 20190918 2
Bayesian inference for coupled hidden Markov models frequently relies on data augmentation techniques for imputation of the hidden state processes. Considerable progress has been made on developing such techniques, mainly using Markov chain Monte Carlo (MCMC) methods. However, as the dimensionality and complexity of the hidden processes increase some of these methods become inefficient, either because they produce MCMC chains with high autocorrelation or because they become computationally intra ...[more]