Projection Pursuit Based on Gaussian Mixtures and Evolutionary Algorithms

Projection Pursuit (PP) algorithm for dimension reduction based on Gaussian Mixture Models (GMMs) for density estimation using Genetic Algorithms (GAs) to maximise an approximated negentropy index. For more details see Scrucca and Serafini (2019) .


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An R package accompanying the paper Projection pursuit based on Gaussian mixtures and evolutionary algorithms by Luca Scrucca and Alessio Serafini (2018).

Installation

You can install the released version of ppgmmga from CRAN:

install.packages("ppgmmga")

or the development version from GitHub:

# install.packages("devtools")
devtools::install_github("luca-scr/ppgmmga")

Usage

Usage of the main functions and several examples are included in the papers shown in the references section below.

For an intro see the vignette A quick tour of ppgmmga, which is available as

vignette("ppgmmga")

Note that if the package is installed from GitHub the vignette is not automatically created. However, it can be created when installing from GitHub with the code:

devtools::install_github("luca-scr/ppgmmga", build_vignettes = TRUE)

References

Scrucca, L. and Serafini, A. (2018) Projection pursuit based on Gaussian mixtures and evolutionary algorithms. Under review.

News

ppgmmga 1.0.1 (2018-10)

  • Fix a C++ issue.

ppgmmga 1.0.0 (2018-10)

  • Initial release on CRAN.

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("ppgmmga")

1.2 by Alessio Serafini, 2 months ago


https://github.com/luca-scr/ppgmmga


Report a bug at https://github.com/luca-scr/ppgmmga/issues


Browse source code at https://github.com/cran/ppgmmga


Authors: Alessio Serafini [aut, cre] , Luca Scrucca [aut]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports Rcpp, mclust, GA, ggplot2, ggthemes, cli, crayon, utils, stats

Suggests knitr

Linking to Rcpp, RcppArmadillo


See at CRAN