https://github.com/danheck/mcmcprecision

Precision for discrete parameters in transdimensional MCMC
https://github.com/danheck/mcmcprecision

Last synced: 27 days ago
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Precision for discrete parameters in transdimensional MCMC

• Host: GitHub
• URL: https://github.com/danheck/mcmcprecision
• Owner: danheck
• Created: 2017-01-24T17:18:54.000Z (almost 8 years ago)
• Default Branch: master
• Last Pushed: 2022-11-11T00:22:49.000Z (almost 2 years ago)
• Last Synced: 2023-11-20T16:22:34.031Z (12 months ago)
• Language: R
• Size: 460 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
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# MCMCprecision: Precision for discrete parameters in transdimensional MCMC

The R package `MCMCprecision` estimates the precision of the posterior model 

probabilities in transdimensional Markov chain Monte Carlo methods (e.g., 

reversible jump MCMC or product-space MCMC). This is useful for applications of 

transdimensional MCMC such as model selection, mixtures with varying numbers of 

components, change-point detection, capture-recapture models, phylogenetic trees, 

variable selection, and for discrete parameters in MCMC output in general.

To install `MCMCprecision` from GitHub, paste the following code to R 

(dependencies need to be installed manually):

```r

### Dependencies:

# install.packages(c("combinat", "devtools","RcppProgress","RcppArmadillo", "RcppEigen"))

library(devtools)

install_github("danheck/MCMCprecision")

```

To compile C++ code, Windows requires [Rtools](https://cran.r-project.org/bin/windows/Rtools/) 

and Mac [Xcode Command Line Tools](https://www.maketecheasier.com/install-command-line-tools-without-xcode/), respectively. Moreover, on Mac, it might be necessary to install the library `gfortran` 

manually by typing the following into the console ([required to compile the package `RcppArmadillo`](http://thecoatlessprofessor.com/programming/rcpp-rcpparmadillo-and-os-x-mavericks-lgfortran-and-lquadmath-error/)):

```

curl -O http://r.research.att.com/libs/gfortran-4.8.2-darwin13.tar.bz2

sudo tar fvxz gfortran-4.8.2-darwin13.tar.bz2 -C /

```

## Reference

* Heck, D. W., Overstall, A. M., Gronau, Q. F., & Wagenmakers, E.-J. (2017). Quantifying uncertainty in transdimensional Markov chain Monte Carlo using discrete Markov models. *Statistics & Computing*. [doi:10.1007/s11222-018-9828-0](https://dx.doi.org/10.1007/s11222-018-9828-0)

[arxiv:1703.10364](https://arxiv.org/abs/1703.10364)