Package: missPLS
Type: Package
Title: Methods and Reproducible Workflows for Partial Least Squares
        with Missing Data
Version: 0.2.1
Date: 2026-04-07
Depends: R (>= 4.1.0)
Imports: mice, plsRglm, stats, utils, VIM
Suggests: bcv, knitr, mlbench, plsdof, rmarkdown, testthat (>= 3.0.0)
Authors@R: c(
    person("Titin Agustin", "Nengsih", role = "aut"),
    person("Frederic", "Bertrand", role = c("aut", "cre"), email = "frederic.bertrand@lecnam.net"),
    person("Myriam", "Maumy-Bertrand", role = "aut"))
Author: Titin Agustin Nengsih [aut],
  Frederic Bertrand [aut, cre],
  Myriam Maumy-Bertrand [aut]
Maintainer: Frederic Bertrand <frederic.bertrand@lecnam.net>
Description: Methods-first tooling for reproducing and extending the
    partial least squares regression studies on incomplete data described in
    Nengsih et al. (2019) <doi:10.1515/sagmb-2018-0059>. The package
    provides simulation helpers, missingness generators, imputation wrappers,
    component-selection utilities, real-data diagnostics, and reproducible
    study orchestration for Nonlinear Iterative Partial Least Squares (NIPALS)-Partial 
    Least Squares (PLS) workflows.
License: GPL-3
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
Config/testthat/edition: 3
RoxygenNote: 7.3.3
URL: https://fbertran.github.io/missPLS/,
        https://github.com/fbertran/missPLS
BugReports: https://github.com/fbertran/missPLS/issues
NeedsCompilation: no
Packaged: 2026-04-29 20:57:19 UTC; bertran7
Repository: CRAN
Date/Publication: 2026-04-30 07:50:09 UTC
Built: R 4.6.0; ; 2026-04-30 11:26:52 UTC; unix
