Performs classical or nonmetric Multidimensional Scaling analysis of provenance data
MDS(x, ...)# S3 method for default
MDS(x, classical = FALSE, k = 2, ...)
# S3 method for compositional
MDS(x, classical = FALSE, k = 2, ...)
# S3 method for counts
MDS(x, classical = FALSE, k = 2, ...)
# S3 method for distributional
MDS(x, classical = FALSE, k = 2, nb = 0, ...)
# S3 method for varietal
MDS(x, classical = FALSE, k = 2, nb = 0, ...)
an object of class MDS
, i.e. a list containing the
following items:
points
: a two column vector of the fitted configuration
classical
: a boolean flag indicating whether the MDS
configuration was obtained by classical (TRUE
) or nonmetric
(FALSE
) MDS.
diss
: the dissimilarity matrix used for the MDS analysis
stress
: (only if classical=TRUE
) the final stress
achieved (in percent)
an object of class distributional
,
compositional
, counts
, varietal
or
diss
optional arguments
If x
has class distributional
, ...
is passed
on to diss.distributional
.
If x
has class compositional
, ...
is passed on
to diss.compositional
.
If x
has class counts
, ...
is passed on to
diss.counts
.
If x
has class varietal
, ...
is passed on to
diss.varietal
.
Otherwise, ...
is passed on to cmdscale
(if
classical=TRUE
), to isoMDS
(if
classical=FALSE
).
boolean flag indicating whether classical
(TRUE
) or nonmetric (FALSE
) MDS should be used
the desired dimensionality of the solution
number of bootstrap resamples. If nb>0
, then
plot.MDS(...)
will visualise the sampling uncertainty as
polygons (inspired by Nordsvan et al. 2020). The bigger
nb
, the slower the calculations. nb=10
seems a
good compromise.
Nordsvan, A.R., Kirscher, U., Kirkland, C.L., Barham, M. and Brennan, D.T., 2020. Resampling (detrital) zircon age distributions for accurate multidimensional scaling solutions. Earth-Science Reviews, p.103149.
Vermeesch, P., 2013, Multi-sample comparison of detrital age distributions. Chemical Geology v.341, 140-146, doi:10.1016/j.chemgeo.2013.01.010
data(Namib)
plot(MDS(Namib$Major,classical=TRUE))
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