elscal: Elastic Scaling SMACOF

elscalR 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: Transformation configuration distances

  • 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)

See Also

rStressMin

Examples

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


smacofx documentation built on Sept. 22, 2024, 5:07 p.m.