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SOPC: The Sparse Online Principal Component Estimation Algorithm

The sparse online principal component can not only process the online data set, but also obtain a sparse solution of the online data set. The philosophy of the package is described in Guo G. (2022) <doi:10.1007/s00180-022-01270-z>.

Version:0.1.0
Depends:R (≥ 4.1.0)
Imports:elasticnet,magrittr, stats
Suggests:testthat (≥ 3.0.0)
Published:2023-05-07
DOI:10.32614/CRAN.package.SOPC
Author:Guangbao Guo [aut, cre], Chunjie Wei [aut], Guoqi Qian [aut]
Maintainer:Guangbao Guo <ggb11111111 at 163.com>
License:MIT + fileLICENSE
NeedsCompilation:no
CRAN checks:SOPC results

Documentation:

Reference manual:SOPC.html ,SOPC.pdf

Downloads:

Package source: SOPC_0.1.0.tar.gz
Windows binaries: r-devel:SOPC_0.1.0.zip, r-release:SOPC_0.1.0.zip, r-oldrel:SOPC_0.1.0.zip
macOS binaries: r-release (arm64):SOPC_0.1.0.tgz, r-oldrel (arm64):SOPC_0.1.0.tgz, r-release (x86_64):SOPC_0.1.0.tgz, r-oldrel (x86_64):SOPC_0.1.0.tgz
Old sources: SOPC archive

Reverse dependencies:

Reverse imports:DSFM,EFM,SFM

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=SOPCto link to this page.


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