adaptMCMC
R package 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.
Keywords for this software
References in zbMATH (referenced in 6 articles )
Showing results 1 to 6 of 6.
Sorted by year (- Waleed Almutiry, Vineetha Warriyar K V, Rob Deardon: Continuous Time Individual-Level Models of Infectious Disease: a Package EpiILMCT (2020) arXiv
- George G Vega Yon; Paul Marjoram: fmcmc: A friendly MCMC framework (2019) not zbMATH
- Venelin Mitov; Tanja Stadler: Parallel likelihood calculation for phylogenetic comparative models: The SPLITT C++ library (2018) not zbMATH
- Dixit, Anand; Roy, Vivekananda: MCMC diagnostics for higher dimensions using Kullback Leibler divergence (2017)
- Yang, Jinyoung; Rosenthal, Jeffrey S.: Automatically tuned general-purpose MCMC via new adaptive diagnostics (2017)
- Scholten, Lisa; Schuwirth, Nele; Reichert, Peter; Lienert, Judit: Tackling uncertainty in multi-criteria decision analysis -- an application to water supply infrastructure planning (2015) ioport