stop_rpowerstress {stops}

STOPS version of restricted powerstress

Description

STOPS version of restricted powerstress

Usage

stop_rpowerstress(
  dis,
  theta = c(1, 1, 1),
  type = "ratio",
  weightmat = NULL,
  init = NULL,
  ndim = 2,
  itmaxi = 10000,
  ...,
  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 powers; the first two arguments are for kappa and lambda and should be equal (for the fitted distances and observed proximities), the third nu (for the weights). Internally the kappa and lambda are equated. If a scalar is given it is recycled (so all elements of theta are equal); if a vector of length 2 is given, it gets expanded to c(theta[1],theta[1],theta[2]). Defaults to 1 1 1.

type

MDS type. Defaults to "ratio".

weightmat

(optional) a matrix of nonnegative weights

init

(optional) initial configuration

ndim

number of dimensions of the target space

itmaxi

number of iterations. default is 10000.

...

additional arguments to be passed to the fitting procedure powerStressMin

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

• 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