sammonmap function

Sammon Mapping SMACOF

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

sammonmap(
  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

Returns

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

• delta: Observed dissimilarities
• tdelta: Observed explicitly transformed dissimilarities, normalized
• dhat: Observed dissimilarities (dhats), optimally scaled and normalized
• confdist: Transformed configuration distances
• conf: Matrix of fitted configuration
• 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
• stress.m: default stress (stress-1^2)
• tweightmat: weighting matrix atfer transformation (here weightmat/delta)

Examples

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

See Also

rStressMin