cluster {GCDkit} | R Documentation |
Hierarchical cluster analysis on a set of dissimilarities.
cluster(x=NULL,elems="SiO2,TiO2,Al2O3,FeOt,MnO,MgO,CaO,Na2O,K2O",label.by=1,method="average")
x |
numerical matrix with compositional data. |
elems |
numerical columns to be used for cluster analysis, typically major elements. |
method |
the agglomeration method to be employed.
This should be one of (or an unambiguous abbreviation thereof):
|
label.by |
numeric; names for each of the cases (samples). |
Even though a list of major elements is assumed as a default, different
variables can be specified. In GUI, this is done by the function
'selectColumnsLabels
'. Moreover, samples can be selected based on
combination of three searching mechanisms
(by sample name/label, range or a Boolean condition) - see
selectSamples
for details.
The user can also specify a label for the individual samples,
default are their names (label.by = 1
).
For label.by
) > 1, the number indicates a sequence number of the
column in the labels
+ 1.
In GUI, the individual clusters can be identified after the dendrogram is drawn. For each sample falling into the given group, specified information (e.g. Locality, Rock Type and/or Author) can be printed.
For further details on the clustering algorithm, see the R manual entry of
'hclust
'.
None.
Names of existing numeric data columns and not formulae involving these can be handled at this stage. As only complete cases are used for the cluster analysis, missing values are replaced by 0.
Vojtěch Janoušek, vojtech.janousek@geology.cz
'hclust
'
data(sazava) accessVar("sazava") cluster(WR,elems = LILE,method = "ward") cluster(WR,elems = LILE,method = "ward.D",label.by=2)