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.

Maintainer: Nuno Fachada <faken at fakenmc.com>

Author(s): Nuno Fachada*

Install package and any missing dependencies by running this line in your R console:

install.packages("micompr")

Depends R (>= 3.2.0)
Imports utils, graphics, methods, stats
Suggests biotools, MVN, testthat(>=0.8), knitr, deseasonalize
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Package micompr
Materials
URL http://github.com/fakenmc/micompr
Task Views
Version 1.0.1
Published 2016-08-04
License MIT + file LICENSE
BugReports https://github.com/fakenmc/micompr/issues
SystemRequirements
NeedsCompilation no
Citation
CRAN checks micompr check results
Package source micompr_1.0.1.tar.gz