stop_elastic: STOPS versions of elastic scaling models (via smacofSym)

Description

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=delta is -2. Allows for a weight matrix because of smacof.

Usage

stop_elastic(
  dis,
  theta = 1,
  type = "ratio",
  ndim = 2,
  weightmat = 1 - diag(nrow(dis)),
  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
)

Value

A list with the components

stress: the stress-1 (sqrt(stress.m))
stress.m: default normalized stress (used for STOPS)
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
stopobj: the stopobj objects

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. Defaults ot 'ratio'.
ndim: number of dimensions of the target space
weightmat: (optional) a matrix of nonnegative weights (NOT the elscal 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.