stop_lmds {stops}

STOPS version of lMDS

Description

STOPS version of lMDS

Usage

stop_lmds(
  dis,
  theta = c(2, 0.5),
  type = "ratio",
  weightmat = NULL,
  init = NULL,
  ndim = 2,
  itmaxi = 5000,
  ...,
  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 is k (for the neighbourhood), the second tau (for the penalty) . If a scalar is given it is recycled. Defaults to 2 and 0.5.

type

MDS type. Ignored.

weightmat

(not used)

init

(optional) initial configuration

ndim

number of dimensions of the target space

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 structures to look for

strucweight

weight to be used for the structures; defaults to 0.5

strucpars

a list of parameters for the structuredness indices; each list element corresponds to one index in the order of the appeacrance in structure

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

• stress.m: default normalized stress

• stoploss: the weighted loss value

• struc: the structuredness indices

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

• fit: the returned object of the fitting procedure

• stopobj: the stopobj object