Package: FSDAM 2024.7-30

FSDAM: Forward Stepwise Deep Autoencoder-Based Monotone NLDR

FS-DAM performs feature extraction through latent variables identification. Implementation is based on autoencoders with monotonicity and orthogonality constraints.

Authors:Youyi Fong [cre], Jun Xu [aut]

FSDAM_2024.7-30.tar.gz
FSDAM_2024.7-30.zip(r-4.7)FSDAM_2024.7-30.zip(r-4.6)FSDAM_2024.7-30.zip(r-4.5)
FSDAM_2024.7-30.tgz(r-4.6-any)FSDAM_2024.7-30.tgz(r-4.5-any)
FSDAM_2024.7-30.tar.gz(r-4.7-any)FSDAM_2024.7-30.tar.gz(r-4.6-any)
FSDAM_2024.7-30.tgz(r-4.6-emscripten)
 |manual.html✨
card.svg |card.png
FSDAM/json (API)

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

Bug tracker:https://github.com/youyifong/fsdam/issues

Datasets:
  • cc.505 - Select Biomarkers from the HVTN 505 Correlates Analysis
  • hvtn505tier1 - HVTN 505 Immune Correlates Tier 1 Dataset

On CRAN:

Conda:

3.70 score 5 scripts 188 downloads 2 exports 13 dependencies

Last updated from:16ef6dddbb. Checks:8 OK, 1 ERROR. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK134
source / vignettesERROR264
linux-release-x86_64OK131
macos-release-arm64OK86
macos-oldrel-arm64OK107
windows-develOK101
windows-releaseOK81
windows-oldrelOK76
wasm-releaseOK92

Exports:fsdamplot.fsdam

Dependencies:herejsonlitekyotillatticeMatrixpngrappdirsRcppRcppTOMLreticulaterlangrprojrootwithr

Forward Stepwise Deep Autoencoder-based Montone Nonlinear Dimensionality Reduction

Rendered fromFSDAM-vignette.pdf.asisusingR.rsp::asison May 11 2026.

Last update: 2025-07-23
Started: 2025-07-23