eqr094: Hierarchical MCMC for Bayesian System Reliability
نویسنده
چکیده
Hierarchical models are one of the central tools of Bayesian analysis. They offer many advantages, including the ability to borrow strength to estimate individual parameters and the ability to specify complex models that reflect engineering and physical realities. Markov chain Monte Carlo is a set of algorithms that allow Bayesian inference in a variety of models. We illustrate hierarchical models and Markov chain Monte Carlo in a
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