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. This package is described in Fachada et al. (2016) <doi:10.32614/RJ-2016-055>.
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micomprmultivariatemultivariate-datamultivariate-distributionsmultivariate-observationsnon-parametricparametric-testsstatistical-analysisstatistical-datastatistical-methodsstatistical-tests
6.00 score 3 stars 55 scripts 228 downloads
clugenr - Multidimensional Cluster Generation Using Support Lines
An implementation of the clugen algorithm for generating multidimensional clusters with arbitrary distributions. Each cluster is supported by a line segment, the position, orientation and length of which guide where the respective points are placed. This package is described in Fachada & de Andrade (2023) <doi:10.1016/j.knosys.2023.110836>.
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multidimensional-clustersmultidimensional-datasynthetic-clusterssynthetic-data-generatorsynthetic-dataset-generation
5.82 score 5 stars 19 scripts 222 downloads