Package: OSIRCR 0.2.9

OSIRCR: Cosine Regression-Based Online Sliced Inverse Regression Algorithm

In high-dimensional streaming data analysis, extracting core periodic features under real-time constraints remains challenging. Traditional dimension reduction methods fail to adapt to incremental data and yield low accuracy due to irrelevant variables. This package provides the Online Sliced Inverse Regression framework for cosine regression with high-dimensional irrelevant variables. It integrates subspace extraction of sliced inverse regression and incremental learning of online algorithms to efficiently handle periodic streaming data. Cai, Z., Li, R., & Zhu, L. (2020) <doi:10.48550/arXiv.2002.02795>.

Authors:Guangbao Guo [aut, cre], Sirui Yan [aut]

OSIRCR_0.2.9.tar.gz
OSIRCR_0.2.9.zip(r-4.7)OSIRCR_0.2.9.zip(r-4.6)OSIRCR_0.2.9.zip(r-4.5)
OSIRCR_0.2.9.tgz(r-4.6-any)OSIRCR_0.2.9.tgz(r-4.5-any)
OSIRCR_0.2.9.tar.gz(r-4.7-any)OSIRCR_0.2.9.tar.gz(r-4.6-any)
OSIRCR_0.2.9.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
OSIRCR/json (API)

# Install 'OSIRCR' in R:
install.packages('OSIRCR', repos = c('https://guangbaog.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • bsir_batch_data - Batch SIR method. This method can estimate batch dimension reduction.
  • opca_online_data - Online PCA method. This method can estimate online eigen space.
  • osir_gd_data - OSIR Gradient Descent method. This method can estimate online dimension reduction.
  • osir_pd_data - OSIR Perturbation method. This method can estimate online dimension reduction.

On CRAN:

Conda:

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

1.00 score 4 exports 0 dependencies

Last updated from:40ab62e479. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK94
source / vignettesOK142
linux-release-x86_64OK97
macos-release-arm64OK98
macos-oldrel-arm64OK72
windows-develOK52
windows-releaseOK56
windows-oldrelOK55
wasm-releaseOK80

Exports:BSIROPCAOSIRgdOSIRpd

Dependencies: