Projection pursuit based on Gaussian mixtures and evolutionary algorithms for data visualisation

An R package implementing a Projection Pursuit (PP) algorithm based on finite Gaussian Mixture Models (GMMs) for density estimation using Genetic Algorithms (GAs) to maximise an approximated negentropy index. The ppgmmga algorithm provides a method to visualise high-dimensional data in a lower-dimensional space.

Details

An introduction to ppgmmga package is provided in the accompaying vignette A quick tour of ppgmmga.

Author

Serafini A. srf.alessio@gmail.com
Scrucca L. luca.scrucca@unipg.it

See also

ppgmmga, plot.ppgmmga, ppgmmga-class, ppgmmga.options, summary.ppgmmga

References

Scrucca, L. and Serafini, A. (2019) Projection pursuit based on Gaussian mixtures and evolutionary algorithms. Journal of Computational and Graphical Statistics, 28:4, 847–860. DOI: 10.1080/10618600.2019.1598871