This uses an approximation to power stress that can make use of smacof as workhorse. Free parameters are tau and upsilon.
cop_apstress(
dis,
theta = c(1, 1, 1),
ndim = 2,
weightmat = NULL,
init = NULL,
itmaxi = 1000,
...,
stressweight = 1,
cordweight = 0.5,
q = 1,
minpts = ndim + 1,
epsilon = 10,
rang = NULL,
verbose = 0,
normed = TRUE,
scale = "sd",
stresstype = "default"
)
A list with the components
stress: the stress
stress.m: default normalized stress
copstress: the weighted loss value
OC: the Optics cordillera value
parameters: the parameters used for fitting (kappa, lambda)
fit: the returned object of the fitting procedure (which has all smacofB elements and some more
cordillera: the cordillera object
numeric matrix or dist object of a matrix of proximities
the theta vector of parameters to optimize over. Must be of length two, with the first the tau argument and the second the upsilon argument. It can also be a scalar of the tau and upsilon transformation for the observed proximities and gets recycled for both ups and tau (so they are equal). Defaults to 1 1.
number of dimensions of the target space
(optional) a binary matrix of nonnegative weights
(optional) initial configuration
number of iterations. default is 1000.
additional arguments to be passed to the fitting procedure
weight to be used for the fit measure; defaults to 1
weight to be used for the cordillera; defaults to 0.5
the norm of the cordillera; defaults to 1
the minimum points to make up a cluster in OPTICS; defaults to ndim+1
the epsilon parameter of OPTICS, the neighbourhood that is checked; defaults to 10
range of the distances (min distance minus max distance). If NULL (default) the cordillera will be normed to each configuration's maximum distance, so an absolute value of goodness-of-clusteredness.
numeric value hat prints information on the fitting process; >2 is extremely verbose
should the cordillera be normed; defaults to TRUE
should the configuration be scale adjusted
which stress to report. Only takes smacofs default stress currrently.