smacofx (version 1.21-1)

opmds: Nonlinear ratio MDS with optimal power of dissimilarities

Description

An implementation to minimize explicitly normalized stress over dissimilarities to a power by majorization with ratio optimal scaling in an alternating minimization algorithm. The optimal power transformation lambda of the dissimilarities is found by an inner optimization step via the Brent-Dekker method.

Usage

opmds(
  delta,
  type = "ratio",
  weightmat = 1 - diag(nrow(delta)),
  init = NULL,
  ndim = 2,
  itmax = 1000,
  acc = 1e-10,
  verbose = FALSE,
  principal = FALSE,
  interval = c(0, 4)
)

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: Transformed fitted configuration distances

• iord: optimal scaling ordering

• conf: Matrix of fitted configuration

• stress: Default stress (stress 1; sqrt of explicitly normalized stress)

• spp: Stress per point

• 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: transformed weighting matrix (here NULL)

• pars, theta: The optimal transformation parameter lambda

Arguments

delta

dist object or a symmetric, numeric data.frame or matrix of distances

type

what type of MDS to fit. Currently only "ratio".

weightmat

a matrix of finite weights.

init

starting configuration

ndim

dimension of the configuration; defaults to 2

itmax

maximum number of iterations. Default is 10000.

acc

numeric accuracy of the iteration. Default is 1e-6.

verbose

should iteration output be printed; defaults to 'FALSE'.

principal

If 'TRUE', principal axis transformation is applied to the final configuration.

interval

the line constraints c(upper, lower), within which to look for the optimal power transformation lambda. Defaults to c(0,4).

See Also

See stops for a similar, more flexible idea.

Examples

dis<-smacof::kinshipdelta
res<-opmds(dis,itmax=1000)
res
summary(res)
plot(res)