MdsDiss {FreeSortR}

Mds of a dissimilarity matrix

Description

Computes the multidimensional scaling of a matrix of dissimilarities between stimuli. Mds is based on smacof algorithm. The Mds configuration is rotated in order to get orthogonal dimensions sorted by decreasing variance.

Usage

MdsDiss(MatDissimil, ndim = 2, metric = TRUE, ties = "primary",
              itmax = 5000, eps = 1e-06)

Arguments

MatDissimil

A matrix of dissimilarities

ndim

Dimension of the Mds

metric

Metric or not metric Mds

ties

Treatment of ties in case of non metric Mds

itmax

Maximum number of iterations

eps

Epsilon for Mds computation

Value

List of the following components :

Config

Mds configuration of the stimuli

Percent

Percentage of inertia of the dimensions of Mds

Stress

Stress of the Mds solution

Examples

  data(AromaSort)
  Aroma<-SortingPartition(AromaSort)
  ListDissimil<-Dissimil(Aroma)
  MatDissim<-apply(simplify2array(ListDissimil),c(1,2),'sum')
  Mdsres<-MdsDiss(MatDissim)