adaptMCMC
R package that provides an implementation of the generic adaptive Monte Carlo Markov chain sampler proposed by Vihola (2011).
Science Score: 23.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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○codemeta.json file
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○.zenodo.json file
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✓DOI references
Found 2 DOI reference(s) in README -
○Academic publication links
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✓Committers with academic emails
1 of 4 committers (25.0%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (4.9%) to scientific vocabulary
Repository
R package that provides an implementation of the generic adaptive Monte Carlo Markov chain sampler proposed by Vihola (2011).
Basic Info
- Host: GitHub
- Owner: scheidan
- License: gpl-2.0
- Language: R
- Default Branch: master
- Size: 40 KB
Statistics
- Stars: 10
- Watchers: 3
- Forks: 6
- Open Issues: 2
- Releases: 0
Metadata Files
README.md
adaptMCMC
R package that provides an implementation of the generic adaptive Monte Carlo Markov chain sampler proposed by Vihola (2011).
Getting started
```R library(adaptMCMC)
---------------------
Define (non-normalized) log density
log-pdf to sample from
p.log <- function(x) { B <- 0.03 # controls 'bananacity' -x[1]^2/200 - 1/2(x[2]+Bx[1]^2-100*B)^2 }
----------------------
generate samples
1) non-adaptive sampling
samp.1 <- MCMC(p.log, n=200, init=c(0, 1), scale=c(1, 0.1), adapt=FALSE)
2) adaptive sampling
samp.2 <- MCMC(p.log, n=200, init=c(0, 1), scale=c(1, 0.1), adapt=TRUE, acc.rate=0.234)
----------------------
summarize results
str(samp.2) summary(samp.2$samples)
covariance of last jump distribution
samp.2$cov.jump
plot chains and marginals
plot(convert.to.coda(samp.2)) ```
References
Vihola, M., 2011. Robust adaptive Metropolis algorithm with coerced acceptance rate. Statistics and Computing. https://doi.org/10.1007/s11222-011-9269-5
Owner
- Name: Andreas Scheidegger
- Login: scheidan
- Kind: user
- Website: http://www.eawag.ch/en/aboutus/portrait/organisation/staff/profile/andreas-scheidegger/
- Repositories: 68
- Profile: https://github.com/scheidan
GitHub Events
Total
- Watch event: 1
Last Year
- Watch event: 1
Committers
Last synced: about 2 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| Andreas Scheidegger | a****r@e****h | 19 |
| Ian Taylor | i****r@c****u | 3 |
| Andreas Scheidegger | s****r@g****m | 1 |
| scheidan | s****a@g****m | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 11 months ago
All Time
- Total issues: 6
- Total pull requests: 2
- Average time to close issues: about 1 year
- Average time to close pull requests: 11 days
- Total issue authors: 3
- Total pull request authors: 2
- Average comments per issue: 1.83
- Average comments per pull request: 4.5
- Merged pull requests: 1
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- scheidan (3)
- venelin (2)
- arnab13061989 (1)
Pull Request Authors
- venelin (1)
- ianmtaylor1 (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
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Total downloads:
- cran 749 last-month
- Total docker downloads: 42,128
- Total dependent packages: 7
- Total dependent repositories: 8
- Total versions: 8
- Total maintainers: 1
cran.r-project.org: adaptMCMC
Implementation of a Generic Adaptive Monte Carlo Markov Chain Sampler
- Homepage: https://github.com/scheidan/adaptMCMC
- Documentation: http://cran.r-project.org/web/packages/adaptMCMC/adaptMCMC.pdf
- License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
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Latest release: 1.0.3
published about 14 years ago
Rankings
Maintainers (1)
Dependencies
- Matrix * depends
- R >= 2.14.1 depends
- coda * depends
- parallel * depends
- ramcmc * imports