confEllipse {smacof} | R Documentation |
Pseudo Confidence Ellipses
Description
Computes pseudo-confidence ellipses for symmetric and individual difference MDS fits.
Usage
## S3 method for class 'smacofID'
confEllipse(object)
## S3 method for class 'confell'
plot(x, eps = 0.05, plot.dim = c(1,2), col = 1,
label.conf = list(label = TRUE, pos = 3, cex = 0.8),
ell = list(lty = 1, lwd = 1, col = 1), main, xlab, ylab, xlim, ylim,
asp = 1, type = "p", pch = 20, ...)
Arguments
object |
Object of class |
x |
Object of class |
eps |
Perturbation region (e.g. 0.05 means that we look at a perturbation region where stress is at most 5% larger than the minimum we have found). |
plot.dim |
Vector with dimensions to be plotted. |
col |
Color for points. |
label.conf |
List with arguments for plotting the labels of the configurations in a configuration plot (logical value whether to plot labels or not, label position). If |
ell |
List with arguments for plotting ellipses: line type, line width, color. |
main |
Plot title. |
xlab |
Label of x-axis. |
ylab |
Label of y-axis. |
xlim |
Scale x-axis. |
ylim |
Scale y-axis. |
asp |
Aspect ratio. |
pch |
Plotting symbol for object point. |
type |
Type of plot. |
... |
Additional plotting arguments. |
Details
The confEllipse
function normalizes the dissimilarities and performs a few more iterations to optimize the configuration and the individual diffierence weights. This result is then passed to a function that computes the stress derivatives which are the basis of the ellipses in the plot function. This function works for ratio scaled versions only.
Value
Returns an object belonging to classes "confell"
.
X |
Configuration (group stimulus space for individual difference models) |
h |
Stress derivatives |
s |
Optimized stress (raw value) |
References
Mair, P., Groenen, P. J. F., De Leeuw, J. (2022). More on multidimensional scaling in R: smacof version 2, Journal of Statistical Software, 102(10), 1-47. doi:10.18637/jss.v102.i10
See Also
Examples
## Simple ratio MDS fit
delta <- sim2diss(cor(PVQ40agg))
res <- mds(delta, ndim = 3)
cres <- confEllipse(res)
plot(cres, plot.dim = c(1,2))
plot(cres, plot.dim = c(1,3))
plot(cres, plot.dim = c(2,3))
## INDSCAL on Helm data
fit1 <- indscal(helm)
cfit1 <- confEllipse(fit1)
plot(cfit1, ell = list(col = "gray", lty = 2), ylim = c(-0.04, 0.04))
## IDIOSCAL on Helm data
fit2 <- idioscal(helm)
cfit2 <- confEllipse(fit2)
plot(cfit1, ell = list(col = "gray", lty = 2), ylim = c(-0.04, 0.04))