| indscal {provenance} | R Documentation |
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 |
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)