smacofSphere {smacof} | R Documentation |
Spherical SMACOF
Description
Dual and primal approach for spherical SMACOF.
Usage
smacofSphere(delta, ndim = 2, type = c("ratio", "interval", "ordinal","mspline"),
algorithm = c("dual", "primal"), weightmat = NULL,
init = "torgerson", ties = "primary", verbose = FALSE, penalty = 100,
relax = FALSE, modulus = 1, itmax = 1000, eps = 1e-6,
spline.degree = 2, spline.intKnots = 2)
Arguments
delta |
Either a symmetric dissimilarity matrix or an object of class |
ndim |
Number of dimensions |
type |
MDS type: |
algorithm |
Algorithm type (see details) |
weightmat |
Optional matrix with dissimilarity weights |
init |
Either |
ties |
Tie specification for non-metric MDS only |
verbose |
If |
penalty |
Penalty parameter for dual algorithm (larger 0), see details |
relax |
If |
modulus |
Number of smacof iterations per monotone regression call |
itmax |
Maximum number of iterations |
eps |
Convergence criterion |
spline.degree |
Degree of the spline for |
spline.intKnots |
Number of interior knots of the spline for |
Details
For large scale problems it is suggested to use the dual algorithm. Using the penalty parameter (dual algorithm), the user allow for slight point deviations from the circle (the higher the penalty, the stricter the algorithm is in terms of placing points in the sphere, see examples section below).
Value
delta |
Observed dissimilarities |
obsdiss |
Observed dissimilarities, normalized |
obsdiss1 |
Dual SMACOF: Observed dissimilarities |
obsdiss2 |
Dual SMACOF: Restriction matrix |
confdist |
Configuration dissimilarities |
conf |
Matrix with fitted configurations |
spp |
Stress per point |
resmat |
Matrix with squared residuals |
rss |
Residual sum-of-squares |
stress |
Stress-1 value |
init |
Starting configurations |
ndim |
Number of dimensions |
dummyvec |
Dummy vector of restriction matrix |
model |
Type of smacof model |
niter |
Number of iterations |
nobj |
Number of objects |
Author(s)
Jan de Leeuw and Patrick Mair
References
De Leeuw, J. & Mair, P. (2009). Multidimensional scaling using majorization: The R package smacof. Journal of Statistical Software, 31(3), 1-30, doi:10.18637/jss.v031.i03
See Also
smacofRect
, smacofIndDiff
, smacofSym
,smacofConstraint
Examples
## spherical SMACOF solution for trading data
## dual algorithm
res <- smacofSphere(trading, type = "ordinal")
res
plot(res)
## lower penalty
res <- smacofSphere(trading, penalty = 20, type = "ordinal")
res
plot(res)
## primal algorithm, interval
res <- smacofSphere(trading, type = "interval", algorithm = "primal")
res