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Efficient Sampling Using Metropolis Algorithms: Applications of Optimal Scaling Results
Journal of Computational And Graphical Statistics
We recently considered the optimal scaling problem of Metropolis algorithms for multidimensional target distributions with non-IID components. The results that were proven have wide applications and the aim of this paper is to show how practitioners can take advantage of them. In particular, we illustrate with several examples the case where the asymptotically optimal acceptance rate is the usual 0.234, and also the latest developments where smaller acceptance rates should be adopted fordoi:10.1198/108571108x319970 fatcat:ox3l7wtuzvcl5pdos3t7wbe6qi