R: Power Stress SMACOF

powerStressMin {smacofx}

R Documentation

Power Stress SMACOF

Description

An implementation to minimize power stress by majorization with ratio or interval optimal scaling. Usually more accurate but slower than powerStressFast. Uses a repeat loop.

Usage

powerStressMin(
  delta,
  kappa = 1,
  lambda = 1,
  nu = 1,
  type = "ratio",
  weightmat = 1 - diag(nrow(delta)),
  init = NULL,
  ndim = 2,
  acc = 1e-06,
  itmax = 10000,
  verbose = FALSE,
  principal = FALSE
)

powerstressMin(
  delta,
  kappa = 1,
  lambda = 1,
  nu = 1,
  type = "ratio",
  weightmat = 1 - diag(nrow(delta)),
  init = NULL,
  ndim = 2,
  acc = 1e-06,
  itmax = 10000,
  verbose = FALSE,
  principal = FALSE
)

postmds(
  delta,
  kappa = 1,
  lambda = 1,
  nu = 1,
  type = "ratio",
  weightmat = 1 - diag(nrow(delta)),
  init = NULL,
  ndim = 2,
  acc = 1e-06,
  itmax = 10000,
  verbose = FALSE,
  principal = FALSE
)

pstressMin(
  delta,
  kappa = 1,
  lambda = 1,
  nu = 1,
  type = "ratio",
  weightmat = 1 - diag(nrow(delta)),
  init = NULL,
  ndim = 2,
  acc = 1e-06,
  itmax = 10000,
  verbose = FALSE,
  principal = FALSE
)

pStressMin(
  delta,
  kappa = 1,
  lambda = 1,
  nu = 1,
  type = "ratio",
  weightmat = 1 - diag(nrow(delta)),
  init = NULL,
  ndim = 2,
  acc = 1e-06,
  itmax = 10000,
  verbose = FALSE,
  principal = FALSE
)

pstressmds(
  delta,
  kappa = 1,
  lambda = 1,
  nu = 1,
  type = "ratio",
  weightmat = 1 - diag(nrow(delta)),
  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
`kappa`	power of the transformation of the fitted distances; defaults to 1
`lambda`	the power of the transformation of the proximities; defaults to 1
`nu`	the power of the transformation for weightmat; defaults to 1
`type`	what type of MDS to fit. One of "ratio" or "interval". Default is "ratio".
`weightmat`	a matrix of finite weights or dist object
`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
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 weighthingmatrix (here weightmat^nu)

Examples

dis<-smacof::kinshipdelta
res<-powerStressMin(dis,type="ratio",kappa=2,lambda=1.5,itmax=1000)
res
summary(res)
plot(res)