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SLFPCA: Sparse Logistic Functional Principal Component Analysis

Implementation for sparse logistic functional principal component analysis (SLFPCA). SLFPCA is specifically developed for functional binary data, and the estimated eigenfunction can be strictly zero on some sub-intervals, which is helpful for interpretation. The crucial function of this package is SLFPCA().

Version: 3.0
Imports: fda, fdapace, psych, splines, stats
Published: 2022-12-13
DOI: 10.32614/CRAN.package.SLFPCA
Author: Rou Zhong [aut, cre], Jingxiao Zhang [aut]
Maintainer: Rou Zhong <zhong_rou at 163.com>
License: GPL (≥ 3)
NeedsCompilation: no
CRAN checks: SLFPCA results

Documentation:

Reference manual: SLFPCA.pdf

Downloads:

Package source: SLFPCA_3.0.tar.gz
Windows binaries: r-devel: SLFPCA_3.0.zip, r-release: SLFPCA_3.0.zip, r-oldrel: SLFPCA_3.0.zip
macOS binaries: r-release (arm64): SLFPCA_3.0.tgz, r-oldrel (arm64): SLFPCA_3.0.tgz, r-release (x86_64): SLFPCA_3.0.tgz, r-oldrel (x86_64): SLFPCA_3.0.tgz
Old sources: SLFPCA archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.