CLCA with free lambda0 and 20 epochs. Should we add alpha0?
stop_clca(
dis,
theta = 3 * max(sd(dis)),
type = "ratio",
weightmat = 1 - diag(nrow(dis)),
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"),
registry = struc_reg
)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 (tau)
fit: the returned object of the fitting procedure
stopobj: the stopobj object
numeric matrix or dist object of a matrix of proximities
the theta vector of explicit parameters; lambda0 for the maximal neighbourhood. Defaults to 100.
MDS type.
(optional) a matrix of nonnegative weights
(optional) initial configuration
number of dimensions of the target space
number of iterations
additional arguments to be passed to the fitting procedure
weight to be used for the fit measure; defaults to 1
a character vector listing the structure indices to use. They always are called "cfoo" with foo being the structure.
weight to be used for the structures; defaults to 1/number of structures
a list of parameters for the structuredness indices; each list element corresponds to one index in the order of the appearance in structures
numeric value hat prints information on the fitting process; >2 is extremely verbose
which weighting to be used in the multi-objective optimization? Either 'additive' (default) or 'multiplicative'.
registry object with c-structuredness indices.