stop_powerstress {stops} | R Documentation |
STOPS version of powerstress
Description
Power stress with free kappa and lambda and rho.
Usage
stop_powerstress(
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 is kappa (for the fitted distances), the second lambda (for the observed proximities), the third nu (for the weights). If a scalar is given it is recycled. Defaults to 1 1 1. |
type |
MDS type. |
weightmat |
(optional) a matrix of nonnegative weights |
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 |
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 parameters for the structuredness indices; each list element corresponds to one index in the order of the appearance in structures |
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