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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 |
| Reference manual: | SLFPCA.pdf |
| 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 |
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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.