Free parameter is lambda for the observed proximities. Fitted distances are transformed with power 2, weights have exponent of 1. Note that the lambda here works as a multiplicator of 2 (as sstress has f(delta^2)).
dis: numeric matrix or dist object of a matrix of proximities
theta: the theta vector of powers; this must be a scalar of the lambda transformation for the observed proximities. Defaults to 1. Note that the lambda here works as a multiplicator of 2 (as sstress has f(delta^2)).
type: MDS type.
weightmat: (optional) a matrix of nonnegative weights
init: (optional) initial configuration
ndim: the 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 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
stoptype: How to construct the target function for the multi objective optimization? Either 'additive' (default) or 'multiplicative'
registry: registry object with c-structuredness indices.
Returns
A list with the components
stress: the stress-1 value
stress.m: default normalized stress
stoploss: the weighted loss value
indices: the values of the structuredness indices
parameters: the parameters used for fitting (lambda)