stop_cmdscale: STOPS version of strain

Description

The free parameter is lambda for power transformations of the observed proximities.

Usage

stop_cmdscale(
  dis,
  theta = 1,
  type = "ratio",
  weightmat = NULL,
  ndim = 2,
  init = NULL,
  ...,
  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"),
  itmaxi = 1000,
  add = TRUE,
  registry = struc_reg
)

Value

A list with the components

stress: the badness-of-fit value (this isn't stress here but 1-(sum_ndim(max(eigenvalues,0))/sum_n(max(eigenvalues,0)), 1-GOF[2])
stress.m: explictly normalized stress (manually calculated)
stoploss: the weighted loss value
indices: the values of the structuredness indices
parameters: the parameters used for fitting (lambda)
fit: the returned object of the fitting procedure, which is cmdscalex object with some extra slots for the parameters and stresses
stopobj: the stopobj object

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.
type: MDS type. Ignored here.
weightmat: (optional) a matrix of nonnegative weights. Not used.
ndim: number of dimensions of the target space
init: (optional) initial configuration
...: 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'
itmaxi: number of iterations. No effect here.
add: if TRUE dis is made to Euclidean distances
registry: registry object with c-structuredness indices.