Implements the template ICA (independent components analysis) model proposed in Mejia et al. (2020) <doi:10.1080/01621459.2019.1679638> and the spatial template ICA model proposed in proposed in Mejia et al. (2022) <doi:10.1080/10618600.2022.2104289>. Both models estimate subject-level brain as deviations from known population-level networks, which are estimated using standard ICA algorithms. Both models employ an expectation-maximization algorithm for estimation of the latent brain networks and unknown model parameters. Includes direct support for 'CIFTI', 'GIFTI', and 'NIFTI' neuroimaging file formats.
Version: | 0.9.1 |
Depends: | R (≥ 3.6.0) |
Imports: | abind, fMRItools (≥ 0.4.4), fMRIscrub, foreach, ica, Matrix, matrixStats, methods, pesel, SQUAREM, stats, utils |
Suggests: | ciftiTools (≥ 0.13.2), excursions, RNifti, oro.nifti, gifti, covr, parallel, doParallel, knitr, rmarkdown, INLA, testthat (≥ 3.0.0) |
Published: | 2024-11-21 |
DOI: | 10.32614/CRAN.package.templateICAr |
Author: | Amanda Mejia [aut, cre], Damon Pham [aut], Daniel Spencer [ctb], Mary Beth Nebel [ctb] |
Maintainer: | Amanda Mejia <mandy.mejia at gmail.com> |
BugReports: | https://github.com/mandymejia/templateICAr/issues |
License: | GPL-3 |
URL: | https://github.com/mandymejia/templateICAr |
NeedsCompilation: | yes |
Additional_repositories: | https://inla.r-inla-download.org/R/testing |
Citation: | templateICAr citation info |
Materials: | README NEWS |
CRAN checks: | templateICAr results |
Reference manual: | templateICAr.pdf |
Package source: | templateICAr_0.9.1.tar.gz |
Windows binaries: | r-devel: templateICAr_0.9.1.zip, r-release: templateICAr_0.9.1.zip, r-oldrel: templateICAr_0.9.1.zip |
macOS binaries: | r-release (arm64): templateICAr_0.9.1.tgz, r-oldrel (arm64): templateICAr_0.9.1.tgz, r-release (x86_64): templateICAr_0.9.1.tgz, r-oldrel (x86_64): templateICAr_0.9.1.tgz |
Old sources: | templateICAr archive |
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