sammonmap {smacofx} | R Documentation |
Sammon Mapping SMACOF
Description
An implementation to minimize Sammon stress by majorization with ratio and interval optimal scaling. Uses a repeat loop.
Usage
sammonmap(
delta,
type = c("ratio", "interval"),
weightmat,
init = NULL,
ndim = 2,
acc = 1e-06,
itmax = 10000,
verbose = FALSE,
principal = FALSE
)
Arguments
delta |
dist object or a symmetric, numeric data.frame or matrix of distances |
type |
what type of MDS to fit. Currently one of "ratio" and "interval". Default is "ratio". |
weightmat |
a matrix of finite weights |
init |
starting configuration |
ndim |
dimension of the configuration; defaults to 2 |
acc |
numeric accuracy of the iteration. Default is 1e-6. |
itmax |
maximum number of iterations. Default is 10000. |
verbose |
should iteration output be printed; if > 1 then yes |
principal |
If 'TRUE', principal axis transformation is applied to the final configuration |
Value
a 'smacofP' object (inheriting from smacofB, see smacofSym
). It is a list with the components
delta: Observed dissimilarities
tdelta: Observed explicitly transformed dissimilarities, normalized
dhat: Observed dissimilarities (dhats), optimally scaled and normalized
confdist: Configuration dissimilarities
conf: Matrix of fitted configuration
stress: Default stress (stress 1; sqrt of explicitly normalized stress)
spp: Stress per point (based on stress.en)
ndim: Number of dimensions
model: Name of smacof model
niter: Number of iterations
nobj: Number of objects
type: Type of MDS model
weightmat: weighting matrix as supplied
stress.m: default stress (stress-1^2)
tweightmat: weighting matrix atfer transformation (here weightmat/delta)
See Also
Examples
dis<-smacof::kinshipdelta
res<-sammonmap(as.matrix(dis),itmax=1000)
res
summary(res)
plot(res)