Package: ppgmmga
Version: 1.3.1
Date: 2025-09-09
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) <doi:10.1080/10618600.2019.1598871>.
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@unibo.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
Packaged: 2026-10-27 08:53:59 UTC; root
Author: Alessio Serafini [aut] (ORCID:
        <https://orcid.org/0000-0002-8579-5695>), Luca Scrucca [aut,
        cre] (ORCID: <https://orcid.org/0000-0003-3826-0484>)
Maintainer: Luca Scrucca <luca.scrucca@unibo.it>
Repository: https://cran.r-universe.dev
Date/Publication: 2025-09-12 16:36:00 UTC
RemoteUrl: https://github.com/cran/ppgmmga
RemoteRef: HEAD
RemoteSha: 6bc808e6a8b810c2c3a30932961a88b6cc70485a