Package: BiplotML
Title: Logistic Biplot Estimation Using Machine Learning Algorithms
Version: 1.1.1
Date: 2026-04-30
Authors@R: 
    person(given = "Jose Giovany",
           family = "Babativa-Marquez",
           role = c("cre", "aut"),
           email = "jgbabativam@unal.edu.co",
           comment = c(ORCID = "0000-0002-4989-7459"))
Description: Implements methods for fitting logistic biplot models to
    multivariate binary data. The logistic biplot represents individuals
    as points and binary variables as directed vectors in a low-dimensional
    subspace; the orthogonal projection of each individual onto a variable
    vector approximates the expected probability that the corresponding
    characteristic is present. Available fitting methods include conjugate
    gradient algorithms, a coordinate descent Majorization-Minimization
    (MM) algorithm, and a block coordinate descent algorithm based on data
    projection that supports matrices with missing values and allows new
    individuals to be projected as supplementary rows without refitting
    the model. A cross-validation procedure is provided to select the
    number of latent dimensions k.
    References: Babativa-Marquez and Vicente-Villardon (2021)
    <doi:10.3390/math9162015>;
    Vicente-Villardon and Galindo (2006, ISBN:9780470973196).
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.3
Depends: R (>= 4.1.0)
Imports: optimx, RSpectra
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, dplyr (>= 1.0.0),
        tidyr (>= 1.1.0), ggplot2 (>= 3.3.2), ggrepel, pracma, mvtnorm
URL: https://github.com/jgbabativam/BiplotML
BugReports: https://github.com/jgbabativam/BiplotML/issues
NeedsCompilation: no
Packaged: 2026-05-03 14:09:14 UTC; giova
Author: Jose Giovany Babativa-Marquez [cre, aut] (ORCID:
    <https://orcid.org/0000-0002-4989-7459>)
Maintainer: Jose Giovany Babativa-Marquez <jgbabativam@unal.edu.co>
Repository: CRAN
Date/Publication: 2026-05-08 15:42:17 UTC
