fontaine618/aMTM: Adaptive Multiple-Try Metropolis Algorithm
Produces a Monte Carlo sample from a continuous distribution of a random vector using a Markov Chain Monte Carlo (MCMC) algorithm. In particular, an adaptive version of the Multiple-Try Metropolis algorithm of Liu at al. (2001) is implemented: details of the algorithm can be found in Fontaine and Bedard (2019). The sample can then be used to perform a Monte Carlo estimation of the expectation of a function of the random vector and standard MCMC techniques can be done (standard error estimation, diagnostic of convergence, etc.).
Getting started
Browse package contents
Package details |
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| Author | c(person("Simon", "Fontaine", role = "aut", email = "fontaines@dms.umontreal.ca")) |
| Maintainer | Simon Fontaine <fontaines@dms.umontreal.ca> |
| License | GPL-2 |
| Version | 0.1.0 |
| URL | https://github.com/fontaine618/aMTM/ |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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