Optimal scaling of random walk Metropolis algorithms using Bayesian large-sample asymptotics
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High-dimensional limit theorems have been shown useful to derive tuning rules for finding the optimal scaling in random walk Metropolis algorithms. The assumptions under which weak convergence results are proved are, however, restrictive: the target density is... ...
