Package: SOPC 0.1.0

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>.

Authors:Guangbao Guo [aut, cre], Chunjie Wei [aut], Guoqi Qian [aut]

SOPC_0.1.0.tar.gz
SOPC_0.1.0.zip(r-4.5)SOPC_0.1.0.zip(r-4.4)SOPC_0.1.0.zip(r-4.3)
SOPC_0.1.0.tgz(r-4.4-any)SOPC_0.1.0.tgz(r-4.3-any)
SOPC_0.1.0.tar.gz(r-4.5-noble)SOPC_0.1.0.tar.gz(r-4.4-noble)
SOPC_0.1.0.tgz(r-4.4-emscripten)SOPC_0.1.0.tgz(r-4.3-emscripten)
SOPC.pdf |SOPC.html✨
SOPC/json (API)

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

Peer review:

Datasets:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 1 scripts 243 downloads 8 exports 3 dependencies

Last updated 2 years agofrom:2b427ff84c. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 30 2024
R-4.5-winOKOct 30 2024
R-4.5-linuxOKOct 30 2024
R-4.4-winOKOct 30 2024
R-4.4-macOKOct 30 2024
R-4.3-winOKOct 30 2024
R-4.3-macOKOct 30 2024

Exports:%>%IPCOPCPCPPCSAPCSOPCSPC

Dependencies:elasticnetlarsmagrittr