provenance (version 0.2)

indscal: Individual Differences Scaling of provenance data

Description

Performs 3-way Multidimensional Scaling analysis using Carroll and Chang (1970)'s INdividual Differences SCALing method as implemented using De Leeuw and Mair (2011)'s stress majorization algorithm.

Usage

indscal(..., type = "ordinal")

Arguments

...

a sequence of datasets of class DZdata or HMdata

type

is either "ratio", "interval", or "ordinal"

Value

• an object of class INDSCAL, i.e. a list containing the following items:

  delta: Observed dissimilarities

  obsdiss: List of observed dissimilarities, normalized

  confdiss: List of configuration dissimilarities

  conf: List of matrices of final configurations

  gspace: Joint configurations aka group stimulus space

  cweights: Configuration weights

  stress: Stress-1 value

  spp: Stress per point

  sps: Stress per subject (matrix)

  ndim: Number of dimensions

  model: Type of smacof model

  niter: Number of iterations

  nobj: Number of objects

References

de Leeuw, J., & Mair, P. (2009). Multidimensional scaling using majorization: The R package smacof. Journal of Statistical Software, 31(3), 1-30, < http://www.jstatsoft.org/v31/i03/>

Examples

DZ <- read.DZdata(system.file("DZ.csv",package="provenance"))
HM <- read.HMdata(system.file("HM.csv",package="provenance"))
plot(indscal(DZ,HM))