For high-dimensional streaming heavy-tailed elliptical data, traditional sliced inverse regression methods require full offline data and cannot adapt to incremental data arrival. This package implements Online Sliced Inverse Regression for Elliptical Model with Streaming Data (OE-SIR) algorithm with two recursive updating strategies, including offline batch SIR as benchmark, elliptical heavy-tailed data simulator, subspace evaluation metric and batch simulation tools for numerical experiments. Cai, Z., Li, R., & Zhu, L. (2020) <doi:10.48550/arXiv.2002.02795>.
| Version: | 0.3.2 |
| Depends: | R (≥ 3.5.0) |
| Imports: | stats, Matrix, MASS |
| Published: | 2026-09-10 |
| DOI: | 10.32614/CRAN.package.oesir |
| Author: | Sirui Yan [aut], Guangbao Guo [aut, cre] |
| Maintainer: | Guangbao Guo <ggb11111111 at 163.com> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| Language: | en-US |
| CRAN checks: | oesir results |
| Reference manual: | oesir.html , oesir.pdf |
| Package source: | oesir_0.3.2.tar.gz |
| Windows binaries: | r-devel: oesir_0.3.2.zip, r-release: not available, r-oldrel: oesir_0.3.2.zip |
| macOS binaries: | r-release (arm64): not available, r-oldrel (arm64): oesir_0.3.2.tgz, r-release (x86_64): oesir_0.3.2.tgz, r-oldrel (x86_64): oesir_0.3.2.tgz |
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