# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "OSIRCR" in publications use:'
type: software
license: MIT
title: 'OSIRCR: Cosine Regression-Based Online Sliced Inverse Regression Algorithm'
version: 0.2.9
doi: 10.32614/CRAN.package.OSIRCR
abstract: 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) <https://doi.org/10.48550/arXiv.2002.02795>.
authors:
- family-names: Guo
  given-names: Guangbao
  email: ggb11111111@163.com
- family-names: Yan
  given-names: Sirui
  email: yansr0601@163.com
repository: https://guangbaog.r-universe.dev
commit: 40ab62e4790718ab25935cb1a4fb2c5efd34e155
date-released: '2026-05-28'
contact:
- family-names: Guo
  given-names: Guangbao
  email: ggb11111111@163.com