Package: ppgmmga Version: 1.3 Date: 2023-11-17 Title: Projection Pursuit Based on Gaussian Mixtures and Evolutionary Algorithms 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) . Authors@R: c(person("Alessio", "Serafini", role = c("aut"), comment = c(ORCID = "0000-0002-8579-5695"), email = "srf.alessio@gmail.com"), person("Luca", "Scrucca", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-3826-0484"), email = "luca.scrucca@unipg.it")) Depends: R (>= 3.4) Imports: Rcpp (>= 1.0.0), mclust (>= 5.4), GA (>= 3.1), ggplot2 (>= 2.2.1), cli, crayon, utils, stats LinkingTo: Rcpp, RcppArmadillo (>= 0.7) Suggests: knitr (>= 1.8), rmarkdown (>= 2.0) VignetteBuilder: knitr License: GPL (>= 2) URL: https://github.com/luca-scr/ppgmmga BugReports: https://github.com/luca-scr/ppgmmga/issues ByteCompile: true NeedsCompilation: yes Encoding: UTF-8 RoxygenNote: 6.1.1 Repository: https://luca-scr.r-universe.dev Date/Publication: 2024-09-19 18:44:47 UTC RemoteUrl: https://github.com/luca-scr/ppgmmga RemoteRef: HEAD RemoteSha: d31378af99c4c52dae3043d74f49ddca89545354 Packaged: 2026-07-03 16:15:04 UTC; root Author: Alessio Serafini [aut] (ORCID: ), Luca Scrucca [aut, cre] (ORCID: ) Maintainer: Luca Scrucca