R Observatory: Metrics for msPCA version 0.5.1

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

msPCA

0.5.1Package record

Sparse Principal Component Analysis with Multiple Principal Components

0packages depend

4.4Kdownloads / year

97.6%test coverage

13/13flavors OK

Overview

About

Maintained by Jean PauphiletCRAN page ↗GitHub ↗Website ↗Issues ↗

Implements an algorithm for computing multiple sparse principal components of a dataset. The method is based on Cory-Wright and Pauphilet "Sparse PCA with Multiple Components" (2026) doi:10.1287/opre.2023.0598. The algorithm uses an iterative deflation heuristic with a truncated power method applied at each iteration to compute sparse principal components with controlled sparsity.

Changes in 0.5.1

mspca() now records feasibilityConstraintType and nonredundancy in the returned object. nonredundancy holds two r x r matrices, orthogonality (\eqn{|u_t^\top u_s|}) and uncorrelatedness (\eqn{|u_t^\top \Sigma u_s| / \mathrm{tr}(\Sigma)}).
summary.mspca() now displays the feasibilityConstraintType used at fitting and the feasibility violation matrix in nonredundancy instead of recomputing them. Its printed output now names the constraint definition in use and points to the stored matrices for the other one.
New weighting rule for the per-component penalty weights to unify both constraint types and improve convergence.
Uncorrelatedness violations are now normalized by the total variance tr(Sigma), i.e. the pairwise term is |u_t' Sigma u_s| / tr(Sigma). The normalized measure is now invariant to a rescaling of Sigma. This affects mspca(..., feasibilityConstraintType = 1) (the feasibility_violation field, the stopping rule, and the dual step size), feasibility_violation_off(), and the uncorrelatedness matrix in nonredundancy. Numerical results under feasibilityConstraintType = 1 may differ from earlier versions unless the input has tr(Sigma) = 1.
Additional input checks for mspca().
Minor documentation updates and clarification.
Added the snp500 dataset: the market-deflated correlation matrix of daily log-returns for 423 S&P 500 constituents, January 2010 - December 2019 (423 x 423, xz-compressed).
Added a vignette "Case study: sparse factors in S&P 500 returns", a full application of mspca() to snp500 comparing the two non-redundancy constraints.
Added a vignette "Algorithm and implementation notes", documenting the optimization problem, both algorithms, the implicit matrix-vector implementation, computational complexity, and guidance on parameter choices.
Added a website-only article "Benchmarking against other sparse PCA packages", comparing mspca() against seven competing implementations on four real datasets. It lives in vignettes/articles/ and is not part of the CRAN build.
Added replication/, the scripts reproducing the benchmarking and case-study results. Build-ignored.
DESCRIPTION gains Depends: R (>= 3.5), LazyData: true, LazyDataCompression: xz and BugReports.

From NEWS.md in the release

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("msPCA", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("jeanpauphilet/msPCA")

Development version from jeanpauphilet/msPCA. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-mspca

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-msPCA

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-msPCA

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 3.5 min · r-devel-windows-x86_64

Status changes

OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK13 OK2026-06-09
ERROR12 OK, 1 ERROR2026-06-08
OK12 OK2026-04-25

Show 3 earlier changesHide 3 earlier changes

NOTE12 OK, 2 NOTE2026-04-22
ERROR11 OK, 2 NOTE, 1 ERROR2026-04-18
NOTE12 OK, 2 NOTE2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 0.5.1

READMEYes · 1,016 wordsVignettesYes · 3 · dynamicNEWSYes · 100% structured · mentions 0.5.1Citation fileYes · cites a publicationWebsiteYes · pkgdown

The repository also keeps web-only articles.

Help pages: 9
Examples that run: 100%7 run in a plain check
Exported functions with examples: 67%
Documented parameters: 100%
Return-value docs: 100%
Help pages citing references: 11%

Vignettes (3)

How these are measured

Downloads

4.4K

CRAN downloads in the past year

Rank #9,778 · ~12/day · ~366/mo

Releases R versions

Daily download trend is not available in this view yet.

28430 days

1K90 days

4.4K1 year

Compare downloads with other packages →

Also on342 r2u3 autocran

How downloads are counted

Repository

jeanpauphilet/mspca ↗Account: jeanpauphilet

1Stars

0Forks

0Open issues

0Open PRs

6Releases

211Commits

2Commit identities

dimensionality-reductionprincipal-component-analysisr-packagesparse-pca

211 commits · Last activity 2026-08-25 · 0% stars, 30d

Responsiveness

How these are sampled

PRs merged (all time): 100%
Median days to close, 50 most recently updated closed issues: 812
Median days to close, 50 most recently updated closed PRs: 0

Stars over time

2026-07-06 · 12026-07-07 · 1

How these are measured

PracticesBeta

10 development-tooling and community-health practices detected across 7 families in the upstream repository

Checks run against github.com/jeanpauphilet/mspca on 2026-10-21.

Continuous integration (2)

GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel

Governance and community (2)

Contributing guideIssue templates

Docs source (2)

pkgdown

GitHub Pages site last deployed 2026-08-25

pkgdown site last built 2026-08-25

Coverage (1)

Coverage reporting

Show all practicesHide 3 practices

Reproducibility and dev environment (1)

data-raw/

CRAN release process (1)

cran-comments.md

Lint, format, editor (1)

RStudio project

How this is detected·Detection ruleset v4 (2026-10-20)

AI coding toolsBeta

This repository shows signs of AI coding tools.

GitHub Copilotfirst seen on or before 2026-05-14
Commits: at least 1 crediting it in the message

Counts are commits, not lines of code. Commits by a tool's accounts count once across all of its accounts. Commits crediting it are the largest count among its credit lines, a minimum.How this is detected·Detection ruleset v4 (updated 2026-09-27)

Dependencies

Declared dependencies

7 external dependencies (excludes base and recommended)

Installing msPCA adds 2 packages (2 with compiled code, 3.5 MB of source tarballs). Heaviest: Rcpp 1.8 MB, RcppEigen 1.7 MB.

Depends (1)

R >= 3.5

Imports (1)

Rcpp

LinkingTo (2)

Rcpp RcppEigen

Suggests (5)

covrdatasetsknitr rmarkdown testthat

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

Datasets

People & History

People (2)

Jean Pauphilet

Ryan Cory-Wright

Author, Copyright holder

Releases (7)

Pick two releases to compare their code metrics.

0.5.1Latest
record
2026-06-25 · current release · diff ↗
0.5.0
record
2026-06-25 · diff ↗ ·
removed 1 export
print_mspca

added 1 export
variance_explained_perPC
0.4.1
record
2026-06-12 · diff ↗
0.4.0
record
2026-05-22 · diff ↗ ·
removed 2 exports
orthogonality_violation, pairwise_correlation

added 2 exports
feasibility_violation_off, fraction_variance_explained_perPC
0.3.0
record
2026-05-15 · diff ↗ ·
removed 1 export
tpw

added 1 export
tpm
R
R 4.6.0 released · 2026-04-24
0.2.0
record
2026-01-12 · diff ↗ ·
added 1 export
pairwise_correlation
0.1.0
record
2025-12-09
R
R 4.5.0 released · 2025-04-11

Package metadata

First published: 2025-12-09
Total releases: 7 / 1 yrs
License: MIT + file LICENSE OSI
Minimum R: ≥ 3.5
Bundled data: 779 KB / 1 file
Download size: 1.3 MB

Appears in task views

Chemometrics and Computational Physics Machine Learning & Statistical Learning

Cite

Cite this package

Run in R for the authors' entry:

citation("msPCA")

The package provides a citation file, so citation() returns the authors' own entry.

It points to 10.1287/opre.2023.0598.

Cite the R Observatory

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

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for msPCA version 0.5.1 [Data set]. HJJB, LLC. Data release v2026-10-23. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-23, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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