Description Usage Arguments Details Value Author(s) References See Also Examples
View source: R/dendro.variables.R
Get dendrogram for variables of mixed types
1 2 | dendro.variables(data, method = c("associationMeasures", "distcor", "ClustOfVar"),
linkage="ward.D2", associationFun = association, check.psd = TRUE)
|
data |
data frame with variables of interest |
method |
If |
linkage |
agglomeration method used for hierarchical clustering when |
associationFun |
By default, appropriate association measures are chosen for each pair of variables, see |
check.psd |
If |
Clustering of variables can either be done i) similarity-based using measures of association, ii) similarity-based using distance correlation, or iii) by the ClustOfVar approach, which uses principal components analysis for mixed data.
An object of class dendrogram
Manuela Hummel
Hummel M, Edelmann D, Kopp-Schneider A (2017). Clustering of samples and variables with mixed-type data. PLOS ONE, 12(11):e0188274.
Chavent M, Kuentz-Simonet V, Liquet B, Saracco J (2012). ClustOfVar: An R Package for the Clustering of Variables. Journal of Statistical Software, 50:1-16.
association
, similarity.variables
, dist.variables
, dendro.subjects
, mix.heatmap
, hclustvar
1 2 3 4 5 6 7 8 9 10 | data(mixdata)
dend1 <- dendro.variables(mixdata, method="associationMeasures")
plot(dend1)
dend2 <- dendro.variables(mixdata, method="distcor")
plot(dend2)
dend3 <- dendro.variables(mixdata, method="ClustOfVar")
plot(dend3)
|
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