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pcreg

0.1.1Package record

Advanced Methods for Principal Component Analysis and Principal Component Regression

0packages depend
115.7Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

Provides a unified framework for principal component analysis (PCA) and principal component regression (PCR), including standard PCA, sparse PCA, robust PCA, and supervised PCA. The package supports automatic selection of the number of components using cumulative variance and elbow methods and integrates PCA with regression modelling through PCR models. It includes tools for PCA suitability assessment using Bartlett's test of sphericity and the Kaiser-Meyer-Olkin (KMO) measure. Visualisation utilities such as scree plots and biplots are provided for interpretation. The methods are designed to handle multicollinearity, outliers, and high-dimensional data, making them suitable for applied statistical modelling and data analysis. The methodology is based on established approaches described in Jolliffe (2002) doi:10.1007/b98835, Zou et al. (2006) doi:10.1111/j.1467-9868.2005.00503.x, and Hubert et al. (2005) doi:10.1198/004017004000000563.

Install

Health

CRAN checks
13OK
Slowest check: 1.9 min · r-oldrel-windows-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK11 OK2026-06-01
  • ERROR6 OK, 2 ERROR2026-05-30
Advisories

none known

Documentation

In release 0.1.1
READMENoVignettesNoNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION
Help pages
8
Examples that run
100%8 run in a plain check
Exported functions with examples
100%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
0%

Downloads

115.7K
CRAN downloads in the past year
Rank #1,077 · ~317/day · ~9.6K/mo
Daily download trend is not available in this view yet.
75230 days
35.1K90 days
115.7K1 year
Compare downloads with other packages →
Also on18 r2u1 autocran

Dependencies

Declared dependencies
8 external dependencies (excludes base and recommended)

Installing pcreg adds 27 packages (12 with compiled code, 21 MB of source tarballs). Heaviest: ggplot2 6.0 MB, robustbase 2.2 MB, Rcpp 1.8 MB.

Depends (0)
none
LinkingTo (0)
none
Suggests (1)
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

People & History

People (4)
Author, Maintainer since 0.1.0 (2026)
Releases (2)

Pick two releases to compare their code metrics.

  • 0.1.1Latest
    record
    2026-05-31 · current release · diff ↗
  • 0.1.0
    record
    2026-05-29
  • R
    R 4.6.0 released · 2026-04-24

Package metadata

First published
2026-05-29
Total releases
2 / 1 yrs
License
GPL-3 OSI
Download size
12 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("pcreg")
Pandit, D. P., Doss, D. S. G., G R, D. H., & Rahul, D. K. (2026). pcreg: Advanced Methods for Principal Component Analysis and Principal Component Regression (Version 0.1.1) [Computer software]. https://doi.org/10.32614/CRAN.package.pcreg

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for pcreg version 0.1.1 [Data set]. HJJB, LLC. Data release v2026-10-24. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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