Putting Markov chains back into Markov chain Monte Carlo
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Publication:933891
DOI10.1155/2007/98086zbMath1211.60030OpenAlexW2071287779MaRDI QIDQ933891
Richard J. Barker, Matthew R. Schofield
Publication date: 28 July 2008
Published in: Journal of Applied Mathematics and Decision Sciences (Search for Journal in Brave)
Full work available at URL: https://eudml.org/doc/117057
Monte Carlo methods (65C05) Markov chains (discrete-time Markov processes on discrete state spaces) (60J10) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20)
Cites Work
- Unnamed Item
- Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
- A unified capture-recapture framework
- Mixing times with applications to perturbed Markov chains
- Sampling-Based Approaches to Calculating Marginal Densities
- Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
- Parsimonious Modelling of Capture-Mark-Recapture Studies
- Utilization of Capture-Mark-Recapture for the Study of Recruitment and Population Growth Rate
- A General Methodology for the Analysis of Capture-Recapture Experiments in Open Populations
- Explicit estimates from capture-recapture data with both death and immigration-stochastic model
- A note on the multiple-recapture census
- Estimates of survival from the sighting of marked animals
- Modeling Association among Demographic Parameters in Analysis of Open Population Capture–Recapture Data
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