nMDS-class {dimRed} | R Documentation |
An S4 Class implementing Non-Metric Dimensional Scaling.
A non-linear extension of MDS using monotonic regression
fun
A function that does the embedding and returns a dimRedResult object.
stdpars
The standard parameters for the function.
Dimensionality reduction methods are S4 Classes that either be used
directly, in which case they have to be initialized and a full
list with parameters has to be handed to the @fun()
slot, or the method name be passed to the embed function and
parameters can be given to the ...
, in which case
missing parameters will be replaced by the ones in the
@stdpars
.
nMDS can take the following parameters:
A distance function.
The number of embedding dimensions.
Wraps around the
monoMDS
. For parameters that are not
available here, the standard configuration is used.
Kruskal, J.B., 1964. Nonmetric multidimensional scaling: A numerical method. Psychometrika 29, 115-129. https://doi.org/10.1007/BF02289694
Other dimensionality reduction methods:
AutoEncoder-class
,
DRR-class
,
DiffusionMaps-class
,
DrL-class
,
FastICA-class
,
FruchtermanReingold-class
,
HLLE-class
,
Isomap-class
,
KamadaKawai-class
,
MDS-class
,
NNMF-class
,
PCA-class
,
PCA_L1-class
,
UMAP-class
,
dimRedMethod-class
,
dimRedMethodList()
,
kPCA-class
,
tSNE-class
if(requireNamespace("vegan", quietly = TRUE)) {
dat <- loadDataSet("3D S Curve", n = 300)
emb <- embed(dat, "nMDS")
plot(emb, type = "2vars")
}