We propose new control variates for variance reduction in estimation of mean values using the Metropolis-Hastings algorithm. Traditionally, states that are rejected in the Metropolis-Hastings ...
Adaptive Metropolis—Hastings samplers use information obtained from previous draws to tune the proposal distribution automatically and repeatedly. Adaptation needs to be done carefully to ensure ...
Markov Chain Monte Carlo (MCMC) methods allow Bayesian models to be fitted, where prior distributions for the model parameters are specified. By default MLwiN sets diffuse priors which can be used to ...
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