stop_smacofSphere function

STOPS versions of smacofSphere models

The free parameter is lambda for power transformations the observed proximities. The fitted distances power is internally fixed to 1 and the power for the weights is 1.

stop_smacofSphere(
  dis,
  theta = 1,
  type = "ratio",
  ndim = 2,
  weightmat = NULL,
  init = NULL,
  itmaxi = 1000,
  ...,
  stressweight = 1,
  structures = c("cclusteredness", "clinearity", "cdependence", "cmanifoldness",
    "cassociation", "cnonmonotonicity", "cfunctionality", "ccomplexity", "cfaithfulness",
    "cregularity", "chierarchy", "cconvexity", "cstriatedness", "coutlying",
    "cskinniness", "csparsity", "cstringiness", "cclumpiness", "cinequality"),
  strucweight = rep(1/length(structures), length(structures)),
  strucpars,
  verbose = 0,
  stoptype = c("additive", "multiplicative"),
  registry = struc_reg
)

Arguments

• dis: numeric matrix or dist object of a matrix of proximities
• theta: the theta vector of powers; this must be a scalar of the lambda transformation for the observed proximities. Defaults to 1.
• type: MDS type.
• ndim: number of dimensions of the target space
• weightmat: (optional) a matrix of nonnegative weights
• init: (optional) initial configuration
• itmaxi: number of iterations
• ...: additional arguments to be passed to the fitting procedure
• stressweight: weight to be used for the fit measure; defaults to 1
• structures: which structuredness indices to be included in the loss
• strucweight: weight to be used for the structuredness indices; ; defaults to 1/#number of structures
• strucpars: the parameters for the structuredness indices
• verbose: numeric value hat prints information on the fitting process; >2 is extremely verbose
• stoptype: How to construct the target function for the multi objective optimization? Either 'additive' (default) or 'multiplicative'
• registry: registry object with c-structuredness indices.

Returns

A list with the components

• stress: the stress-1 value
• stress.m: default normalized stress
• stoploss: the weighted loss value
• indices: the values of the structuredness indices
• parameters: the parameters used for fitting
• fit: the returned object of the fitting procedure
• stopobj: the stopobj object