powerStressMin function

Power Stress SMACOF

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.

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

Returns

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
• 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)

See Also

smacofSym