https://github.com/nunofachada/micompm

Multivariate independent comparison of observations
https://github.com/nunofachada/micompm

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: 7 months ago
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Multivariate independent comparison of observations

• Host: GitHub
• URL: https://github.com/nunofachada/micompm
• Owner: nunofachada
• License: mit
• Created: 2016-01-10T01:23:11.000Z (over 9 years ago)
• Default Branch: master
• Last Pushed: 2018-07-30T19:05:39.000Z (almost 7 years ago)
• Last Synced: 2024-10-28T04:59:15.571Z (9 months ago)
• 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
• Language: Matlab
• Homepage:
• Size: 365 KB
• Stars: 3
• Watchers: 1
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md

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README

        
[![Latest release](https://img.shields.io/github/release/fakenmc/micompm.svg)](https://github.com/fakenmc/micompm/releases)

[![Documentation](https://img.shields.io/badge/documentation-user_guide-brightgreen.svg)](docs/userguide.md)

[![MIT Licence](https://img.shields.io/badge/license-MIT-yellowgreen.svg)](https://opensource.org/licenses/MIT/)

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.931838.svg)](https://doi.org/10.5281/zenodo.931838)

[![JOSS](http://joss.theoj.org/papers/10.21105/joss.00430/status.svg)](https://doi.org/10.21105/joss.00430)

### Summary

_micompm_ is a [MATLAB]/[Octave] port of the original [micompr] [R] 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

* [MATLAB Statistics toolbox] / [Octave statistics package]

### Documents

* [User Guide]

* [Contributing guidelines](CONTRIBUTING.md)

* [Code of conduct](CODE_OF_CONDUCT.md)

### 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](http://arxiv.org/abs/1509.09174))

### License

[MIT License](LICENSE)

[micompr]: https://github.com/fakenmc/micompr

[R]: https://www.r-project.org/

[MATLAB]: http://www.mathworks.com/products/matlab/

[Octave]: https://gnu.org/software/octave/

[User Guide]: docs/userguide.md

[MATLAB Statistics toolbox]: https://www.mathworks.com/products/statistics.html

[Octave statistics package]: https://octave.sourceforge.io/statistics/