cica
Code repository of the R package Clusterwise Independent Component Analysis
Science Score: 36.0%
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Low similarity (14.0%) to scientific vocabulary
Keywords
Repository
Code repository of the R package Clusterwise Independent Component Analysis
Basic Info
Statistics
- Stars: 2
- Watchers: 2
- Forks: 1
- Open Issues: 1
- Releases: 7
Topics
Metadata Files
README.md
Clusterwise Independent Component Analysis R package
Version notes
Version of CICA on CRAN notes:
- CRAN v0.1.0: CICA version with ALS random start procedure
- CRAN v1.1.1: CICA version with all working functionalities, including EVD based estimation procedure.
Version of CICA on GitHub:
Download the development version of CICA using the devtools package: devtools::install_github('jeffreydurieux/CICA')
This version contains:
R v0.1.0: CICA version with ALS random start procedure
R v0.2.1: CICA with (pseudo-) rational start options
- v0.2.0: modified RV matrix computations (computeRVmat()). A (dis) similarity matrix is computed between a list of input matrices. This is based on the two-step clustering procedure from Durieux & Wilderjans (2019).
- v0.2.0: FindRationalStarts() function. This function applies the two-step procedure using several hierarchical clustering methods in order to find rational starts for the ALS algorithm for CICA. Cluster perturbation options are also included. This function returns an object of class
rstarts. This object can be passed to the CICA main function. - v0.2.0: These options are also directly included in the CICA main function.
- v0.2.1: Update of example data. Added a single example data set from the simulation design of Durieux & Wilderjans (2019). It contains 60 subjects and original cluster specific components and the true simulated clustering is added.
R v0.3.0 CICA version with multiple CICA models
R v1.0.0 CICA version with all working functionalities. This version is also available on CRAN. This package version includes the papayar archived files that were made by John Muschelli.
R v1.1.1 CICA version with a fast EVD based estimation procedure. This results in an equal (or similar) clustering. Use the final clustering to seed the CICA (using method = 'fastICA') to extract independent components.
Owner
- Name: Jeffrey Durieux
- Login: jeffreydurieux
- Kind: user
- Location: The Netherlands
- Company: Leiden University
- Website: www.jeffreydurieux.com
- Repositories: 6
- Profile: https://github.com/jeffreydurieux
GitHub Events
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Last Year
Committers
Last synced: over 2 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| jeffreydurieux | d****y@g****m | 66 |
| Jeffrey Durieux | j****x | 40 |
Issues and Pull Requests
Last synced: over 2 years ago
All Time
- Total issues: 13
- Total pull requests: 2
- Average time to close issues: 8 months
- Average time to close pull requests: less than a minute
- Total issue authors: 1
- Total pull request authors: 1
- Average comments per issue: 0.54
- Average comments per pull request: 0.0
- Merged pull requests: 2
- 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
- jeffreydurieux (13)
Pull Request Authors
- jeffreydurieux (2)
Top Labels
Issue Labels
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Dependencies
- NMFN * depends
- R >= 2.10 depends
- RNifti * depends
- ica * depends
- papayar * depends
- plotly * depends