Package: sRDA 1.0.0

sRDA: Sparse Redundancy Analysis

Sparse redundancy analysis for high dimensional (biomedical) data. Directional multivariate analysis to express the maximum variance in the predicted data set by a linear combination of variables of the predictive data set. Implemented in a partial least squares framework, for more details see Csala et al. (2017) <doi:10.1093/bioinformatics/btx374>.

Authors:Attila Csala [aut, cre], Koos Zwinderman [ctb]

sRDA_1.0.0.tar.gz
sRDA_1.0.0.zip(r-4.7-any)sRDA_1.0.0.zip(r-4.6-any)sRDA_1.0.0.zip(r-4.5-any)
sRDA_1.0.0.tgz(r-4.6-any)sRDA_1.0.0.tgz(r-4.5-any)
sRDA_1.0.0.tar.gz(r-4.7-any)sRDA_1.0.0.tar.gz(r-4.6-any)
sRDA_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
sRDA/json (API)

# Install 'sRDA' in R:
install.packages('sRDA', repos = c('https://acsala.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/acsala/srda/issues

On CRAN:

Conda:

3.18 score 3 stars 8 scripts 242 downloads 3 exports 9 dependencies

Last updated from:7bc9fbb423. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK101
source / vignettesOK173
linux-releaseOK113
macos-releaseOK200
macos-oldrelOK158
windows-develOK70
windows-releaseOK69
windows-oldrelOK85
wasm-releaseOK83

Exports:generate_datasCCAsRDA

Dependencies:codetoolsdoParallelelasticnetforeachiteratorslarslatticeMatrixmvtnorm