PCovR
2.7.2Principal Covariates Regression
Overview
Analyzing regression data with many and/or highly collinear predictor variables, by simultaneously reducing the predictor variables to a limited number of components and regressing the criterion variables on these components (de Jong S. & Kiers H. A. L. (1992) doi:10.1016/0169-7439(92)80100-I). Several rotation and model selection options are provided.
Install
Health
- NOTE r-devel-linux-x86_64-debian-clang
- NOTE r-devel-linux-x86_64-debian-gcc
- NOTE2026-03-1012 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- not tracked
- Return-value docs
- not tracked
- References docs
- 90%
Downloads
Dependencies
Code & Tests
Datasets
People & History
Author records are not tracked yet for this package.
12 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- 2.7.2Latest
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- 2.7.12021-01-29 · diff ↗
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- RR 3.5.0 released · 2018-04-23
- 2.72017-06-19 · diff ↗
- RR 3.4.0 released · 2017-04-21
- RR 3.3.0 released · 2016-05-03
- 2.62015-05-05 · diff ↗
- RR 3.2.0 released · 2015-04-16
Package metadata
- First published
- 2013-03-20
- Total releases
- 12 / 13 yrs
- License
- GPL (>= 2) OSI
- Bundled data
- 3.8 KB / 2 files
- Download size
- 19 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("PCovR")Cite the R Observatory
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