micompm

micompm: A MATLAB/Octave toolbox for multivariate independent comparison of observations - Published in JOSS (2018)

https://github.com/nunofachada/micompm

Science Score: 49.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 11 DOI reference(s) in README
  • Academic publication links
    Links to: arxiv.org, joss.theoj.org, zenodo.org
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (12.9%) to scientific vocabulary

Keywords

matlab matlab-toolbox multivariate multivariate-data multivariate-distributions multivariate-observations non-parametric octave octave-functions octave-scripts parametric-tests statistical-analysis statistical-data statistical-methods statistical-tests
Last synced: 6 months ago · JSON representation

Repository

Multivariate independent comparison of observations

Basic Info
  • Host: GitHub
  • Owner: nunofachada
  • License: mit
  • Language: Matlab
  • Default Branch: master
  • Homepage:
  • Size: 365 KB
Statistics
  • Stars: 3
  • Watchers: 1
  • Forks: 2
  • Open Issues: 0
  • Releases: 3
Topics
matlab matlab-toolbox multivariate multivariate-data multivariate-distributions multivariate-observations non-parametric octave octave-functions octave-scripts parametric-tests statistical-analysis statistical-data statistical-methods statistical-tests
Created about 10 years ago · Last pushed over 7 years ago
Metadata Files
Readme Contributing License Code of conduct

README.md

Latest release Documentation MIT Licence DOI JOSS

Summary

micompm is a MATLAB/Octave port of the original micompr package for comparing multivariate samples associated with different groups. It uses principal component analysis to convert multivariate observations into a set of linearly uncorrelated statistical measures, which are then compared using a number of statistical methods. This technique is independent of the distributional properties of samples and automatically selects features that best explain their differences, avoiding manual selection of specific points or summary statistics. The procedure is appropriate for comparing samples of time series, images, spectrometric measures or similar multivariate observations. It is aimed at researchers from all fields of science, although it requires some knowledge on design of experiments, statistical testing and multidimensional data analysis.

Follow micompm's User Guide to get started.

Dependencies

Documents

References

Practice

  • Fachada N, Rosa AC. (2018) micompm: A MATLAB/Octave toolbox for multivariate independent comparison of observations. Journal of Open Source Software. 3(23):430. https://doi.org/10.21105/joss.00430

Theory

  • Fachada N, Lopes VV, Martins RC, Rosa AC. (2017) Model-independent comparison of simulation output. Simulation Modelling Practice and Theory. 72:131–149. http://dx.doi.org/10.1016/j.simpat.2016.12.013 (arXiv preprint)

License

MIT License

Owner

  • Name: Nuno Fachada
  • Login: nunofachada
  • Kind: user
  • Location: Portugal
  • Company: Universidade Lusófona

Professor @VideojogosLusofona

GitHub Events

Total
Last Year

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 109
  • Total Committers: 3
  • Avg Commits per committer: 36.333
  • Development Distribution Score (DDS): 0.046
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Nuno Fachada f****n@f****m 104
Nuno Fachada f****c 4
jordigh j****h@o****g 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 2
  • Total pull requests: 1
  • Average time to close issues: 4 months
  • Average time to close pull requests: less than a minute
  • Total issue authors: 1
  • Total pull request authors: 1
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • nunofachada (2)
Pull Request Authors
  • nunofachada (1)
Top Labels
Issue Labels
enhancement (1)
Pull Request Labels