micompr: Multivariate Independent Comparison of Observations

A procedure 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. The procedure 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. It is appropriate for comparing samples of time series, images, spectrometric measures or similar multivariate observations.

Version: 1.0.2
Depends: R (≥ 3.2.0)
Imports: utils, graphics, methods, stats
Suggests: biotools, MVN, deseasonalize, testthat (≥ 0.8), knitr, roxygen2, devtools
Published: 2017-06-24
Author: Nuno Fachada [aut, cre]
Maintainer: Nuno Fachada <faken at fakenmc.com>
BugReports: https://github.com/fakenmc/micompr/issues
License: MIT + file LICENSE
URL: http://github.com/fakenmc/micompr
NeedsCompilation: no
Citation: micompr citation info
Materials: README
CRAN checks: micompr results

Downloads:

Reference manual: micompr.pdf
Vignettes: micompr: An R Package for Multivariate Independent Comparison of Observations
Examples of generated Latex tables
Package source: micompr_1.0.2.tar.gz
Windows binaries: r-devel: micompr_1.0.1.zip, r-release: micompr_1.0.1.zip, r-oldrel: micompr_1.0.1.zip
OS X El Capitan binaries: r-release: micompr_1.0.1.tgz
OS X Mavericks binaries: r-oldrel: micompr_1.0.1.tgz
Old sources: micompr archive

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