Science Score: 39.0%
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 2 DOI reference(s) in README -
○Academic publication links
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○Committers with academic emails
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (12.7%) to scientific vocabulary
Keywords
bayesian-inference
covariance-matrix-estimation
empirical-bayes
graphical-models
high-dimensional-inference
machine-learning
network-analysis
precision-matrix-estimation
statistics
Last synced: 6 months ago
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JSON representation
Repository
Fast Bayesian inference in large graphical models.
Statistics
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 0
- Releases: 2
Topics
bayesian-inference
covariance-matrix-estimation
empirical-bayes
graphical-models
high-dimensional-inference
machine-learning
network-analysis
precision-matrix-estimation
statistics
Created over 7 years ago
· Last pushed 6 months ago
Metadata Files
Readme
Changelog
README.md
beam
Fast Bayesian inference of network structures.
Features
- inference of conditional independence structures
- inference of marginal independence structures
- computationally efficient (no MCMC)
- memory-efficient
- able to address problems with thousands of variables on a standard laptop in just a few seconds
- outperforms popular Bayesian and non-Bayesian methods
Installation
To install beam from R:
```R
Install/load R package devtools
install.packages("devtools") library(devtools)
Install/load R package beam from github
install_github("gleday/beam") library(beam) ```
Citation
This R package implements the method described in
Leday, G.G.R. and Richardson, S. (2019). Fast Bayesian inference in large Gaussian graphical models. Biometrics. 75(4), 1288--1298.
Owner
- Name: Gwenael Leday
- Login: gleday
- Kind: user
- Location: Wageningen, The Netherlands
- Company: Wageningen University & Research
- Repositories: 2
- Profile: https://github.com/gleday
Biostatistician
GitHub Events
Total
- Push event: 7
- Pull request event: 2
- Fork event: 1
Last Year
- Push event: 7
- Pull request event: 2
- Fork event: 1
Committers
Last synced: almost 3 years ago
All Time
- Total Commits: 60
- Total Committers: 2
- Avg Commits per committer: 30.0
- Development Distribution Score (DDS): 0.383
Top Committers
| Name | Commits | |
|---|---|---|
| gleday | g****y@g****m | 37 |
| “gwenael.leday@gmail.com” | “****” | 23 |
Packages
- Total packages: 1
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Total downloads:
- cran 314 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 7
- Total maintainers: 1
cran.r-project.org: beam
Fast Bayesian Inference in Large Gaussian Graphical Models
- Homepage: https://github.com/gleday/beam
- Documentation: http://cran.r-project.org/web/packages/beam/beam.pdf
- License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2.0)]
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Latest release: 2.0.4
published 11 months ago
Rankings
Forks count: 28.8%
Dependent packages count: 29.8%
Average: 34.4%
Stargazers count: 35.2%
Dependent repos count: 35.5%
Downloads: 42.7%
Maintainers (1)
Last synced:
6 months ago
Dependencies
DESCRIPTION
cran
- R >= 3.1.0 depends
- Matrix * imports
- Rcpp * imports
- assertthat * imports
- fdrtool * imports
- grDevices * imports
- graphics * imports
- igraph * imports
- knitr * imports
- methods * imports
- stats * imports
- covr * suggests
- testthat * suggests