R/PCA.OS.R

In martinparies/PCAOS: PCA.OS

#' PCA.OS
#'
#' The PCA.OS pacakge allows for single and multi-block exploratory analysis of variables of different nature. It allows both the dimension reduction and the quantification of datasets trough Optimal Scaling. Main functions are PCAOS for Principal Component Analysis with Optimal Scaling features and MBPCAOS for Multiblock version.
#'
#' @docType package
#'
#' @details
#' \itemize{
#'   \item Package : PCA.OS
#'   \item Version : 0.1
#'   \item Date : 14/12/2021
#'   \item License :
#' }
#'
#' @author
#' \itemize{
#'   \item Martin PARIES (Maintainer: \email{martin.paries@oniris-nantes.fr})
#'   \item Evelyne Vigneau
#'   \item Stephanie Bougeard
#' }
#'
#' @references
#' De Leeuw, J. (2013). History of nonlinear principal component analysis. eScholarship, University of California.
#'
#' @import stats
#' @import graphics
#' @import ggplot2
#' @import ggpubr
#' @import ggpubr
#'
#' @name PCA.OS
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