https://github.com/ardiad/admit

Adaptive Mixture of Student-t distributions
https://github.com/ardiad/admit

adaptive distribution fitting mcmc mixture mixture-model

Last synced: about 1 month ago
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Adaptive Mixture of Student-t distributions

• Host: GitHub
• URL: https://github.com/ardiad/admit
• Owner: ArdiaD
• License: gpl-2.0
• Created: 2016-05-28T09:38:49.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2022-02-07T23:48:42.000Z (almost 3 years ago)
• Last Synced: 2024-10-28T17:24:18.130Z (2 months ago)
• Topics: adaptive, distribution, fitting, mcmc, mixture, mixture-model
• Language: R
• Size: 5.19 MB
• Stars: 2
• Watchers: 3
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: COPYING

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README

        
# AdMit

`AdMit` ([Ardia et al., 2009a](https://doi.org/10.18637/jss.v029.i03)) is an R package which provides 

flexible functions to approximate a certain target distribution and to efficiently generate a sample of 

random draws from it, given only a kernel of the target density function. The core 

algorithm fits an adaptive mixture of Student-t distributions to the density of interest, and then, 

importance sampling or the independence chain Metropolis-Hastings algorithm is used to obtain 

quantities of interest for the target density, using the fitted mixture as the importance or 

candidate density. The estimation procedure is fully automatic and thus avoids the 

time-consuming and difficult task of tuning a sampling algorithm.

Full description of the algorithm and numerous applications are available in [Ardia et al. (2009a)](https://doi.org/10.18637/jss.v029.i03) and [Ardia et al. (2009b)](https://doi.org/10.32614/RJ-2009-003).

## Please cite the package in publications!

By using `AdMit` you agree to the following rules: 

1) You must cite [Ardia et al. (2009a)](https://doi.org/10.18637/jss.v029.i03) in working papers and published papers that use `AdMit`.

2) You must place the following URL in a footnote to help others find `AdMit`: [https://CRAN.R-project.org/package=AdMit](https://CRAN.R-project.org/package=AdMit). 

3) You assume all risk for the use of `AdMit`.

Ardia, D., Hoogerheide, L., van Dijk, H.K. (2009a).    

Adaptive mixture of Student-t distributions as a flexible candidate 

distribution for efficient simulation: The R package AdMit.    

_Journal of Statistical Software_, 29(3), 1-32.     

[https://doi.org/10.18637/jss.v029.i03](https://doi.org/10.18637/jss.v029.i03)  

Ardia, D., Hoogerheide, L., van Dijk, H.K. (2009b).    

AdMit: Adaptive mixture of Student-t distributions.   

_R Journal_, 1(1), 25-30.     

[https://doi.org/10.32614/RJ-2009-003](https://doi.org/10.32614/RJ-2009-003)