R: Elastic Scaling SMACOF

elscal {smacofx}

R Documentation

Elastic Scaling SMACOF

Description

An implementation to minimize elastic scaling stress by majorization with ratio and interval optimal scaling. Uses a repeat loop.

Usage

elscal(
  delta,
  type = c("ratio", "interval"),
  weightmat,
  init = NULL,
  ndim = 2,
  acc = 1e-06,
  itmax = 10000,
  verbose = FALSE,
  principal = FALSE
)

Arguments

`delta`	dist object or a symmetric, numeric data.frame or matrix of distances
`type`	what type of MDS to fit. Currently one of "ratio" and "interval". Default is "ratio".
`weightmat`	a matrix of finite weights
`init`	starting configuration
`ndim`	dimension of the configuration; defaults to 2
`acc`	numeric accuracy of the iteration. Default is 1e-6.
`itmax`	maximum number of iterations. Default is 10000.
`verbose`	should iteration output be printed; if > 1 then yes
`principal`	If 'TRUE', principal axis transformation is applied to the final configuration

Value

a 'smacofP' object (inheriting from smacofB, see smacofSym). It is a list with the components

delta: Observed untransformed dissimilarities
tdelta: Observed explicitly transformed dissimilarities, normalized
dhat: Explicitly transformed dissimilarities (dhats), optimally scaled and normalized
confdist: Configuration dissimilarities, NOT normalized
conf: Matrix of fitted configuration, NOT normalized
stress: Default stress (stress 1; sqrt of explicitly normalized stress)
spp: Stress per point (based on stress.en)
ndim: Number of dimensions
model: Name of smacof model
niter: Number of iterations
nobj: Number of objects
type: Type of MDS model
weightmat: weighting matrix as supplied
tweightmat: transformed weighting matrix (here weightmat/delta^2)
stress.m: Default stress (stress-1^2)

Examples

dis<-smacof::kinshipdelta
res<-elscal(as.matrix(dis),itmax=1000)
res
summary(res)
plot(res)