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ppgmmga  

Projection Pursuit Based on Gaussian Mixtures and Evolutionary Algorithms
View on CRAN: Click here


Download and install ppgmmga package within the R console
Install from CRAN:
install.packages("ppgmmga")

Install from Github:
library("remotes")
install_github("cran/ppgmmga")

Install by package version:
library("remotes")
install_version("ppgmmga", "1.3")



Attach the package and use:
library("ppgmmga")
Maintained by
Luca Scrucca
[Scholar Profile | Author Map]
First Published: 2018-10-14
Latest Update: 2019-07-08
Description:
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) .
How to cite:
Luca Scrucca (2018). ppgmmga: Projection Pursuit Based on Gaussian Mixtures and Evolutionary Algorithms. R package version 1.3, https://cran.r-project.org/web/packages/ppgmmga. Accessed 13 Apr. 2025.
Previous versions and publish date:
1.0.1 (2018-10-15 20:20), 1.0 (2018-10-14 17:30), 1.1 (2019-06-03 15:00), 1.2 (2019-07-08 11:10)
Other packages that cited ppgmmga R package
View ppgmmga citation profile
Other R packages that ppgmmga depends, imports, suggests or enhances
Complete documentation for ppgmmga
Functions, R codes and Examples using the ppgmmga R package
Some associated functions: nclass.numpy . plot.ppgmmga . ppgmmga-class . ppgmmga-internal . ppgmmga-package . ppgmmga . ppgmmga.options . summary.ppgmmga . 
Some associated R codes: RcppExports.R . functions.R . options.R . plots.R . ppgmmga.R . zzz.R .  Full ppgmmga package functions and examples
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