nMDS-class {dimRed} | R Documentation |
Non-Metric Dimensional Scaling
Description
An S4 Class implementing Non-Metric Dimensional Scaling.
Details
A non-linear extension of MDS using monotonic regression
Slots
fun
A function that does the embedding and returns a dimRedResult object.
stdpars
The standard parameters for the function.
General usage
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
.
Parameters
nMDS can take the following parameters:
- d
A distance function.
- ndim
The number of embedding dimensions.
Implementation
Wraps around the
monoMDS
. For parameters that are not
available here, the standard configuration is used.
References
Kruskal, J.B., 1964. Nonmetric multidimensional scaling: A numerical method. Psychometrika 29, 115-129. https://doi.org/10.1007/BF02289694
See Also
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
Examples
if(requireNamespace("vegan", quietly = TRUE)) {
dat <- loadDataSet("3D S Curve", n = 300)
emb <- embed(dat, "nMDS")
plot(emb, type = "2vars")
}