stop_apstress {stops}

STOPS version of approximated power stress models.

Description

This uses an approximation to power stress that can make use of smacof as workhorse. Free parameters are kappa, lambda and nu.

Usage

stop_apstress(
  dis,
  theta = c(1, 1, 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")
)

Arguments

dis

numeric matrix or dist object of a matrix of proximities

theta

the theta vector of parameters to optimize over. Must be of length three, with the first the kappa argument, the second the lambda argument and the third the nu argument. One cannot supply upsilon and tau as of yet. Defaults to 1 1 1.

type

MDS type.

ndim

number of dimensions of the target space

weightmat

(optional) a binary matrix of nonnegative weights

init

(optional) initial configuration

itmaxi

number of iterations. default is 1000.

...

additional arguments to be passed to the fitting procedure

stressweight

weight to be used for the fit measure; defaults to 1

structures

a character vector listing the structure indices to use. They always are called "cfoo" with foo being the structure.

strucweight

weight to be used for the structures; defaults to 1/number of structures

strucpars

a list of list of parameters for the structuredness indices; each list element corresponds to one index in the order of the appearance in structures vector. See examples.

verbose

numeric value hat prints information on the fitting process; >2 is extremely verbose

stoptype

which weighting to be used in the multi-objective optimization? Either 'additive' (default) or 'multiplicative'.

Value

A list with the components

• stress: the stress-1 value (sqrt stress.m)

• stress.m: default normalized stress

• stoploss: the weighted loss value

• struc: the structuredness indices

• parameters: the parameters used for fitting (kappa, lambda, nu)

• fit: the returned object of the fitting procedure

• stopobj: the stopobj object