rStressMin | R Documentation |
An implementation to minimize r-stress by majorization with ratio, interval, monotonic spline and ordinal optimal scaling. Uses a repeat loop.
rStressMin(
delta,
r = 0.5,
type = c("ratio", "interval", "ordinal", "mspline"),
ties = "primary",
weightmat = 1 - diag(nrow(delta)),
init = NULL,
ndim = 2,
acc = 1e-06,
itmax = 10000,
verbose = FALSE,
principal = FALSE,
spline.degree = 2,
spline.intKnots = 2
)
rstressMin(
delta,
r = 0.5,
type = c("ratio", "interval", "ordinal", "mspline"),
ties = "primary",
weightmat = 1 - diag(nrow(delta)),
init = NULL,
ndim = 2,
acc = 1e-06,
itmax = 10000,
verbose = FALSE,
principal = FALSE,
spline.degree = 2,
spline.intKnots = 2
)
rstressmds(
delta,
r = 0.5,
type = c("ratio", "interval", "ordinal", "mspline"),
ties = "primary",
weightmat = 1 - diag(nrow(delta)),
init = NULL,
ndim = 2,
acc = 1e-06,
itmax = 10000,
verbose = FALSE,
principal = FALSE,
spline.degree = 2,
spline.intKnots = 2
)
rstress(
delta,
r = 0.5,
type = c("ratio", "interval", "ordinal", "mspline"),
ties = "primary",
weightmat = 1 - diag(nrow(delta)),
init = NULL,
ndim = 2,
acc = 1e-06,
itmax = 10000,
verbose = FALSE,
principal = FALSE,
spline.degree = 2,
spline.intKnots = 2
)
delta |
dist object or a symmetric, numeric data.frame or matrix of distances |
r |
power of the transformation of the fitted distances (corresponds to kappa/2 in power stress); defaults to 0.5 for standard stress |
type |
what type of MDS to fit. Currently one of "ratio", "interval", "mspline" or "ordinal". Default is "ratio". |
ties |
the handling of ties for ordinal (nonmetric) MDS. Possible are "primary" (default), "secondary" or "tertiary". |
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 fitting information be printed; if > 0 then yes |
principal |
If 'TRUE', principal axis transformation is applied to the final configuration |
spline.degree |
Degree of the spline for ‘mspline’ MDS type |
spline.intKnots |
Number of interior knots of the spline for ‘mspline’ MDS type |
a 'smacofP' object (inheriting from 'smacofB', see smacofSym
). It is a list with the components
delta: Observed, untransformed dissimilarities
tdelta: Observed explicitly transformed dissimilarities, normalized
dhat: Explicitly transformed dissimilarities (dhats), optimally scaled and normalized
confdist: Transformed fitted configuration distances
iord: Optimally scaled disparities function
conf: Matrix of fitted configuration
stress: Default stress (stress 1; sqrt of explicitly normalized stress)
spp: Stress per point
ndim: Number of dimensions
weightmat: Weighting matrix as supplied
resmat: Residual matrix
rss: Sum of residuals
init: The starting configuration
model: Name of MDS model
niter: Number of iterations
nobj: Number of objects
type: Type of optimal scaling
call : the matched call
stress.m: Default stress (stress-1^2)
alpha: Alpha matrix
sigma: Stress
parameters, pars, theta: Optimal transformation parameter
tweightmat: Transformed weighting matrix (here NULL)
smacofSym
dis<-smacof::kinshipdelta
## ordinal MDS
res<-rStressMin(as.matrix(dis), type = "ordinal", r = 1, itmax = 1000)
res
summary(res)
plot(res)
## spline MDS
ress<-rStressMin(as.matrix(dis), type = "mspline", r = 1,
itmax = 1000)
ress
plot(ress,"Shepard")
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