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 + file LICENSE
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, DTFM, EFM, SFM

Linking:

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