indscal: Individual Differences Scaling of provenance data

In provenance: Statistical Toolbox for Sedimentary Provenance Analysis

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", itmax = 1000)

Arguments

...	a sequence of datasets of class distributional, compositional, counts or varietal, OR a single object of class varietal.
type	is either "ratio" or "ordinal"
itmax	Maximum number of iterations

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

Author(s)

Jan de Leeuw and Patrick Mair

References

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

Examples

## Not run: 
attach(Namib)
plot(indscal(DZ,HM,PT,Major,Trace))

## End(Not run)

provenance documentation built on Aug. 28, 2023, 5:07 p.m.