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.
- Version1.5
- R version≥ 2.14.1 parallel,
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- Last release01/29/2024
Team
Andreas Scheidegger
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