REPPlab: An R package for detecting clusters and outliers using exploratory projection pursuit

Abstract

The R-package REPPlab is designed to explore multivariate data sets using one-dimensional unsupervised projection pursuit. It is useful as a preprocessing step to find clusters or as an outlier detection tool for multivariate data. Except from the packages tourr and rggobi, there is no implementation of exploratory projection pursuit tools available in R. REPPlab is an R interface for the Java program EPP-lab that implements four projection indices and three biologically inspired optimization algorithms. It also proposes new tools for plotting and combining the results and specific tools for outlier detection. The functionality of the package is illustrated through some simulations and using some real data.

Keywords:

• Genetic algorithms
• Java
• Kurtosis
• Particle swarm optimization
• Projection index
• Tribes
• Projection matrix
• Unsupervised data analysis

Acknowledgments

The authors wish to acknowledge CSC – IT Center for Science, Finland, for providing computational resources.

Additional information

Funding

The article is based upon work from COST Action CRoNoS (Grant No. IC1408), supported by COST (European Cooperation in Science and Technology).