Approximated Information Analysis in Bayesian Inference
In models with nuisance parameters, Bayesian procedures based on Markov Chain Monte Carlo (MCMC) methods have been developed to approximate the posterior distribution of the parameter of interest. Because these procedures require burdensome computations related to the use of MCMC, approximation and...
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| Autori principali: | , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
MDPI AG
2015-03-01
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| Serie: | Entropy |
| Soggetti: | |
| Accesso online: | http://www.mdpi.com/1099-4300/17/3/1441 |
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