adaptMCMC: Implementation of a Generic Adaptive Monte Carlo Markov Chain Sampler

Enables sampling from arbitrary distributions if the log density is known up to a constant; a common situation in the context of Bayesian inference. The implemented sampling algorithm was proposed by Vihola (2012) <DOI:10.1007/s11222-011-9269-5> and achieves often a high efficiency by tuning the proposal distributions to a user defined acceptance rate.

Getting started

Package details

AuthorAndreas Scheidegger, <>, <>
MaintainerAndreas Scheidegger <>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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adaptMCMC documentation built on May 1, 2019, 9:51 p.m.