Package: sdwd 1.0.6

sdwd: Sparse Distance Weighted Discrimination

Formulates a sparse distance weighted discrimination (SDWD) for high-dimensional classification and implements a very fast algorithm for computing its solution path with the L1, the elastic-net, and the adaptive elastic-net penalties. More details about the methodology SDWD is seen on Wang and Zou (2016) (<doi:10.1080/10618600.2015.1049700>).

Authors:Boxiang Wang and Hui Zou

sdwd_1.0.6.tar.gz
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sdwd_1.0.6.tgz(r-4.6-x86_64)sdwd_1.0.6.tgz(r-4.6-arm64)sdwd_1.0.6.tgz(r-4.5-x86_64)sdwd_1.0.6.tgz(r-4.5-arm64)
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sdwd_1.0.6.tgz(r-4.5-emscripten)
sdwd.pdf |sdwd.html✨
sdwd/json (API)

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

Bug tracker:https://github.com/boxiang-wang/sdwd/issues

Datasets:
  • colon - Simplified gene expression data from Alon et al.

On CRAN:

Conda:

fortran

2.45 score 14 scripts 250 downloads 2 mentions 18 exports 2 dependencies

Last updated from:53732f03da. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK109
linux-devel-x86_64OK118
source / vignettesOK126
linux-release-arm64OK118
linux-release-x86_64OK120
macos-release-arm64OK79
macos-release-x86_64OK159
macos-oldrel-arm64OK85
macos-oldrel-x86_64OK254
windows-develOK89
windows-releaseOK129
windows-oldrelOK79
wasm-releaseOK91

Exports:coef.cv.sdwdcoef.sdwdcv.sdwdcvcomputeerrerror.barsgetmingetoutputlambda.interplamfixnonzeroplot.cv.sdwdplot.sdwdpredict.cv.sdwdpredict.sdwdprint.sdwdsdwdzeromat

Dependencies:latticeMatrix