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msma

3.1

Multiblock Sparse Multivariable Analysis

1packages depend
2.5Kdownloads / year
test coverage
11/13checks pass

Overview

About
Maintained by Atsushi KawaguchiFirst published 2016-01-019 releasesCRAN page ↗

Several functions can be used to analyze multiblock multivariable data. If the input is a single matrix, then principal components analysis (PCA) is implemented. If the input is a list of matrices, then multiblock PCA is implemented. If the input is two matrices, for exploratory and objective variables, then partial least squares (PLS) analysis is implemented. If the input is two lists of matrices, for exploratory and objective variables, then multiblock PLS analysis is implemented. Additionally, if an extra outcome variable is specified, then a supervised version of the methods above is implemented. For each method, sparse modeling is also incorporated. Functions for selecting the number of components and regularized parameters are also provided.

Install

Health

CRAN checks
2NOTE11OK
Failing flavors
  • NOTE r-devel-linux-x86_64-debian-clang
  • NOTE r-devel-linux-x86_64-debian-gcc
Slowest check: 12.7 min · r-devel-windows-x86_64
Code health
None
Tests · ratio 0.00
not tracked
Coverage
100%
Documentation · exports
0
Dependencies · direct
Check history
  • NOTE2026-06-09
    11 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-06-08
    11 OK · 1 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • NOTE2026-03-10
    12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMENoVignettesYes · dynamicpkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
98%
Return-value docs
100%
References docs
8%

Downloads

2.5K
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63590 days
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Dependencies

Declared dependencies
2 external dependencies (excludes base and recommended)
Depends (1)
R >= 3.5
Imports (0)
none
LinkingTo (0)
none
Suggests (2)
Enhances (0)
none
Reverse dependencies
1direct
0indirect

Code & Tests

People & History

People (0)

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Listed in earlier versions (1)
no longer listed · 0.7 to 3.1
Package Timeline

9 releases. Pick two to compare their code metrics. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • 3.1Latest
    2024-02-14 · current release · diff ↗
  • 3.0
    2023-08-25 · diff ↗
  • R
    R 4.3.0 released · 2023-04-21
  • R
    R 4.2.0 released · 2022-04-22
  • 2.2
    2021-06-25 · diff ↗
  • R
    R 4.1.0 released · 2021-05-18
  • R
    R 4.0.0 released · 2020-04-24
  • 2.1
    2020-02-06 · diff ↗
  • 2.0
    2019-09-01 · diff ↗
  • 1.2
    2019-06-02 · diff ↗
  • R
    R 3.6.0 released · 2019-04-26
  • 1.1
    2018-05-04 · diff ↗
  • R
    R 3.5.0 released · 2018-04-23
Show 5 earlier events
  • 1.0
    2018-03-01 · diff ↗
  • R
    R 3.4.0 released · 2017-04-21
  • R
    R 3.3.0 released · 2016-05-03
  • 0.7
    2016-01-01
  • R
    R 3.2.0 released · 2015-04-16

Package metadata

First published
2016-01-01
Total releases
9 / 10 yrs
License
GPL (>= 2) OSI
Minimum R
≥ 3.5
Download size
675 KB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

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Run in R for the authors' preferred citation:

citation("msma")

Cite the R Observatory

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APA

Balamuta, J. J. (2026). R Observatory: Metrics for msma version 3.1 [Data set]. HJJB, LLC. Data release v2026-08-18. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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