Bayesian inference is a probabilistic inferential method. In the last two decades, it has become more popular than ever due to affordable computing power and recent advances in Markov chain Monte Carlo (MCMC) methods for approximating high dimensional integrals. Bayesian inference can be traced bac
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Bayesian inference of BWR model parameters by Markov chain Monte Carlo
β Scribed by E. Zio; A. Zoia
- Publisher
- Elsevier Science
- Year
- 2008
- Tongue
- English
- Weight
- 367 KB
- Volume
- 35
- Category
- Article
- ISSN
- 0306-4549
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## Abstract A Bayesian modeling and Markov Chain Monte Carlo simulation was developed for a kinetic study of homopolymerization and copolymerization systems at the molecular scale. Two copolymerization models β the terminal unit model and the penultimate unit model β were considered. Prior estimate