stop_rstress {stops} | R Documentation |
STOPS version of rstress
stop_rstress(dis, theta = c(1, 1, 1), weightmat = NULL, init = NULL, ndim = 2, ..., 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, type = c("additive", "multiplicative"))
dis |
numeric matrix or dist object of a matrix of proximities |
theta |
the theta vector of powers; this is either a scalar of the kappa transformation for the fitted distances proximities, or a vector where the first element is taken to be the kappa argument for the fitted distances and the second the lambda argument (internally fixed to 1), the third the nu argument (here internally fixed to 1). Defaults to 1 1 1. Note the kappa here differs from Jan's version where r=kappa/2. |
weightmat |
(optional) a matrix of nonnegative weights |
init |
(optional) initial configuration |
ndim |
number of dimensions of the target space |
... |
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 |
type |
How to construct the target function for the multi objective optimization? Either 'additive' (default) or 'multiplicative' |
A list with the components
stress: the stress
stress.m: default normalized stress
stoploss: the weighted loss value
indices: the values of the structuredness indices
parameters: the parameters used for fitting
fit: the returned object of the fitting procedure
indobj: the index objects