Nothing
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
Browse package contents
Package details |
|
|---|---|
| Author | Andreas Scheidegger, <andreas.scheidegger@eawag.ch>, <scheidegger.a@gmail.com> |
| Maintainer | Andreas Scheidegger <andreas.scheidegger@eawag.ch> |
| License | GPL (>= 2) |
| Version | 1.5 |
| URL | https://github.com/scheidan/adaptMCMC |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the adaptMCMC package in your browser
Any scripts or data that you put into this service are public.
