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.

Package details

AuthorNuno Fachada [aut, cre]
MaintainerNuno Fachada <faken@fakenmc.com>
LicenseMIT + file LICENSE
URL https://github.com/fakenmc/micompr
Package repositoryView on CRAN
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micompr documentation built on May 1, 2019, 9:14 p.m.