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.
Package details 


Maintainer  Nuno Fachada <[email protected]> 
License  MIT + file LICENSE 
Version  1.0.2 
URL  http://github.com/fakenmc/micompr 
Package repository  View on GitHub 
Installation 
Install the latest version of this package by entering the following in R:

Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.