Science Score: 49.0%
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Found 3 DOI reference(s) in README -
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Links to: arxiv.org -
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○Scientific vocabulary similarity
Low similarity (17.0%) to scientific vocabulary
Repository
Group SLOPE (Group Sorted L1 Penalized Estimation)
Basic Info
- Host: GitHub
- Owner: agisga
- License: gpl-3.0
- Language: R
- Default Branch: master
- Homepage: http://agisga.github.io/grpSLOPE/
- Size: 1.57 MB
Statistics
- Stars: 4
- Watchers: 4
- Forks: 2
- Open Issues: 0
- Releases: 7
Metadata Files
README.md
grpSLOPE
Group SLOPE is a penalized linear regression method that is used for adaptive selection of groups of significant predictors in a high-dimensional linear model. A unique feature of the Group SLOPE method is that it offers (group) false discovery rate control (i.e., control of the expected proportion of irrelevant groups among the total number of groups of predictors selected by Group SLOPE). A detailed description of the method can be found in D. Brzyski, A. Gossmann, W. Su, and M. Bogdan (2019) "Group SLOPE — adaptive selection of groups of predictors", Journal of the American Statistical Association (or the 2016 arXiv preprint).
Usage
The basic model fitting procedure for a Group SLOPE model is:
```R library(grpSLOPE)
result <- grpSLOPE(X=X, y=y, group=group, fdr=0.1) ```
where X is the model matrix, y the response vector, group a vector specifying group memberships of the predictor variables, and fdr the target (group) false discovery rate for the variable selection procedure.
One can access various estimated parameters of the fitted model, such as the selected groups, the estimated noise level, or the estimated vector of regression coefficients:
```R
groups that have a non-zero effect
result$selected
noise level
sigma(result)
coefficient vector
coef(result) ```
A detailed basic usage example can be found here.
More complicated (and possibly less helpful) example codes are available in the repository grpSLOPE_examples.
Installation
The latest stable version of grpSLOPE can be installed from CRAN (The Comprehensive R Archive Network). Just open an R session and do:
R
install.packages("grpSLOPE")
Installation of the development version
Your R configuration must allow for a working Rcpp.
The easiest way to install the latest development version of grpSLOPE is by using the R package devtools. Just open up an R session and run:
```R
Install devtools, if you haven't already.
install.packages("devtools")
library(devtools) install_github("agisga/grpSLOPE") ```
If you don't want to use devtools, you can install grpSLOPE by downloading the source code and then following these steps:
- Install the R package
Rcpp. - Go to the directory that contains the
grpSLOPEdirectory (which contains thegrpSLOPEsource code). - Open an R session and run
Rcpp::compileAttributes("./grpSLOPE"). Then quit R. - Run
R CMD build grpSLOPE. You should then have a file likegrpSLOPE_0.2.1.9000.tar.gz. - Run
R CMD INSTALL grpSLOPE_0.2.1.9000.tar.gzto install the package.
Development workflow
- Modify the code.
- Open
grpSLOPE.Rprojwith RStudio. - Run
devtools::document(). - Optionally run
devtools::clean_dll()to clean up old compiled shared objects. - Run
devtools::build(). - Install with
devtools::install(build = TRUE, upgrade = "never"). - Run checks with
devtools::check() - Do
devtools::test()to run the unit tests.
Owner
- Name: Alexej Gossmann
- Login: agisga
- Kind: user
- Website: http://www.alexejgossmann.com/
- Repositories: 58
- Profile: https://github.com/agisga
GitHub Events
Total
- Release event: 1
- Issue comment event: 1
- Push event: 3
- Pull request event: 1
- Create event: 1
Last Year
- Release event: 1
- Issue comment event: 1
- Push event: 3
- Pull request event: 1
- Create event: 1
Committers
Last synced: about 3 years ago
All Time
- Total Commits: 184
- Total Committers: 3
- Avg Commits per committer: 61.333
- Development Distribution Score (DDS): 0.179
Top Committers
| Name | Commits | |
|---|---|---|
| agisga | a****o@g****m | 151 |
| agisga | 1****a@u****m | 32 |
| agisga | a****o@g****m | 1 |
Issues and Pull Requests
Last synced: 8 months ago
All Time
- Total issues: 4
- Total pull requests: 11
- Average time to close issues: over 1 year
- Average time to close pull requests: about 21 hours
- Total issue authors: 1
- Total pull request authors: 2
- Average comments per issue: 0.25
- Average comments per pull request: 0.18
- Merged pull requests: 10
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 1
- Average time to close issues: N/A
- Average time to close pull requests: 5 days
- Issue authors: 0
- Pull request authors: 1
- Average comments per issue: 0
- Average comments per pull request: 1.0
- Merged pull requests: 1
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- agisga (4)
Pull Request Authors
- agisga (9)
- jolars (3)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
-
Total downloads:
- cran 309 last-month
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 7
- Total maintainers: 1
cran.r-project.org: grpSLOPE
Group Sorted L1 Penalized Estimation
- Homepage: https://github.com/agisga/grpSLOPE
- Documentation: http://cran.r-project.org/web/packages/grpSLOPE/grpSLOPE.pdf
- License: GPL-3
-
Latest release: 0.3.4
published 9 months ago
Rankings
Maintainers (1)
Dependencies
- Rcpp * imports
- SLOPE * suggests
- isotone * suggests
- knitr * suggests
- pander * suggests
- rmarkdown * suggests
- testthat * suggests
- actions/checkout v3 composite
- r-lib/actions/check-r-package v2 composite
- r-lib/actions/setup-pandoc v2 composite
- r-lib/actions/setup-r v2 composite
- r-lib/actions/setup-r-dependencies v2 composite