bootmds.smacofP {smacofx} | R Documentation |
MDS Bootstrap for smacofP objects
Description
Performs a bootstrap on an MDS solution. It works for derived dissimilarities only, i.e. generated by the call dist(data). The original data matrix needs to be provided, as well as the type of dissimilarity measure used to compute the input dissimilarities.
Usage
## S3 method for class 'smacofP'
bootmds(
object,
data,
method.dat = "pearson",
nrep = 100,
alpha = 0.05,
verbose = FALSE,
...
)
Arguments
object |
Object of class smacofP if used as method or another object inheriting from smacofB (needs to be called directly as bootmds.smacofP then). |
data |
Initial data (before dissimilarity computation). |
method.dat |
Dissimilarity computation used as MDS input. This must be one of "pearson", "spearman", "kendall", "euclidean", "maximum", "manhattan", "canberra", "binary". |
nrep |
Number of bootstrap replications. |
alpha |
Alpha level for condfidence ellipsoids. |
verbose |
If 'TRUE', bootstrap index is printed out. |
... |
Additional arguments needed for dissimilarity computation as specified in |
Details
In order to examine the stability solution of an MDS, a bootstrap on the raw data can be performed. This results in confidence ellipses in the configuration plot. The ellipses are returned as list which allows users to produce (and further customize) the plot by hand. See bootmds
for more.
Value
An object of class 'smacofboot', see bootmds
. With values
cov: Covariances for ellipse computation
bootconf: Configurations bootstrap samples
stressvec: Bootstrap stress values
bootci: Stress bootstrap percentile confidence interval
spp: Stress per point (based on stress.en)
stab: Stability coefficient
Examples
##see ?smacof::bootmds for more
data <- na.omit(smacof::PVQ40[,1:5])
diss <- dist(t(data)) ## Euclidean distances
fit <- rStressMin(diss,r=0.5,itmax=1000) ## 2D ratio MDS
set.seed(123)
resboot <- bootmds(fit, data, method.dat = "euclidean", nrep = 10) #run for more nrep
resboot
plot(resboot) #see ?smacof::bootmds for more on the plot method