R/yapprox.r

In multisensi: Multivariate Sensitivity Analysis

# Multisensi R package ; file yapprox.r (last modified: 2015-10-15) 
# Authors: C. Bidot, M. Lamboni, H. Monod
# Copyright INRA 2011-2018 
# MaIAGE, INRA, Univ. Paris-Saclay, 78350 Jouy-en-Josas, France
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# More about multisensi in https://CRAN.R-project.org/package=multisensi
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#===========================================================================
yapprox <- function(multivar.obj, nbcomp=2, aov.obj)
#===========================================================================
{
  ## calcule les sorties du modele approxime

  ## INPUTS
  ## multivar.obj : "objet" multivar, sortie de la fonction multivar (liste)
  ## nbcomp       : nombre de composantes a utiliser pour le metamodele
  ## aov.obj      : objet/liste issu de la sortie de la fonction analysis.anoasg

  ## OUTPUTS
  ## echsimul.app : sorties Y approximees sous forme de matrice

  ##recuperation des nbcomp premieres lignes de la matrice inversee des vecteurs propres.
  inv.comp <-  t(multivar.obj$L)[1:nbcomp,,drop=FALSE]
  # multivar.obj$L de taille ncol(Y) x nbcomp++

  ##calcul des sorties approximees des variables (PC.predict)
  echsimul.app <- aov.obj$Hpredict %*% inv.comp
  # aov.obj$Hpredict de taille nrow(Y)*nbcomp

  ## reconstitution des  valeurs de Yapp du fait que les Y utilises pour multivar.obj etaient (ou non) reduits
  echsimul.app <- echsimul.app %*% diag(multivar.obj$scaling,ncol(echsimul.app),ncol(echsimul.app));
  # si normalise, alors scaling=sdY, sinon, scaling=1

  ## decentre
  echsimul.app <- multivar.obj$centering + echsimul.app
  colnames(echsimul.app)=rownames(multivar.obj$L)

  return(echsimul.app)
}