stop_cmdscale {stops} | R Documentation |
STOPS version of strain
stop_cmdscale(dis, theta = c(1, 1, 1), weightmat = NULL, ndim = 2, init = NULL, ..., stressweight = 1, structures = c("cclusteredness", "clinearity", "cdependence", "cmanifoldness", "cassociation", "cnonmonotonicity", "cfunctionality", "ccomplexity", "cfaithfulness", "cregularity"), 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 lambda transformation for the observed proximities, or a vector where the first is the kappa argument for the fitted distances (here internally fixed to 1) and the second and third the lambda and the nu argument (the latter is fixed to 1). Defaults to 1 1 1 |
weightmat |
(optional) a matrix of nonnegative weights |
ndim |
number of dimensions of the target space |
init |
(optional) initial configuration |
... |
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: Not really stress but 1-GOF where GOF is the first element returned from cmdscale (the sum of the first ndim absolute eigenvalues divided by the sum of all absolute eigenvalues)
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