smacofRect {smacof} | R Documentation |
Variant of smacof for rectangular matrices (typically ratings, preferences) which is also known as metric unfolding.
smacofRect(delta, ndim = 2, weightmat = NULL, init = NULL, verbose = FALSE, itmax = 1000, reg = 1e-6, eps = 1e-6)
delta |
Data frame or matrix of preferences, ratings, dissimilarities. |
ndim |
Number of dimensions |
weightmat |
Optional matrix with dissimilarity weights |
init |
Matrix with starting values for configurations (optional) |
verbose |
If |
itmax |
Maximum number of iterations |
reg |
Regularization factor, prevents distances from being 0 |
eps |
Convergence criterion |
Creates an object of class smacofR
.
obsdiss |
Observed dissimilarities, corresponds to delta |
confdiss |
Configuration dissimilarities |
conf.row |
Matrix of final row configurations |
conf.col |
Matrix of final column configurations |
stress |
Final stress value |
spp.row |
Stress per point, rows |
spp.col |
Stress per point, columns |
ndim |
Number of dimensions |
model |
Type of smacof model |
niter |
Number of iterations |
nind |
Number of individuals (rows) |
nobj |
Number of objects (columns) |
Jan de Leeuw and Patrick Mair
de Leeuw, J. & Mair, P. (2009). Multidimensional scaling using majorization: The R package smacof. Journal of Statistical Software, 31(3), 1-30, http://www.jstatsoft.org/v31/i03/
smacofConstraint
, smacofSym
, smacofIndDiff
, smacofSphere.primal
, smacofSphere.dual
, plot.smacof
data(breakfast) res <- smacofRect(breakfast) res summary(res) ## various configuration plots plot(res) plot(res, type = "p", pch = 25) plot(res, type = "p", pch = 25, col.columns = 3, label.conf.columns = list(label = TRUE, pos = 3, col = 3), col.rows = 8, label.conf.rows = list(label = TRUE, pos = 3, col = 8)) plot(res, joint = TRUE) plot(res, joint = TRUE, type = "p", pch = 25, col.columns = 4, label.conf.columns = list(label = TRUE, pos = 3, col = 4), col.rows = 8, label.conf.rows = list(label = TRUE, pos = 3, col = 8))