Selet assets from Multivariate Asset Sets based on clustering.
1  assetsSelect(x, method = c("hclust", "kmeans"), control = NULL, ...)

x 
any rectangular time series object which can be converted by the
function 
method 
a character string, which clustering method should be used?
Either 
control 
a character string with two entries controlling the parameters used
in the underlying cluster algorithms. If set to NULL, then
default settings are taken: For hierarchical clustering this is

... 
optional arguments to be passed. Note, for the kmeans algorithm the number of centers has to be specified! 
The function assetsSelect
calls the functions hclust
or kmeans
from R's "stats"
package. hclust
performs a hierarchical cluster analysis on the set of dissimilarities
hclust(dist(t(x)))
and kmeans
performs a kmeans
clustering on the data matrix itself.
Note, the hierarchical clustering method has in addition a plot method.
if use="hclust"
was selected then the function returns a
S3 object of class "hclust", otherwise if use="kmeans"
was
selected then the function returns an object of class "kmeans".
For details we refer to the help pages of hclust
and
kmeans
.
Diethelm Wuertz for the Rmetrics port.
Wuertz, D., Chalabi, Y., Chen W., Ellis A. (2009); Portfolio Optimization with R/Rmetrics, Rmetrics eBook, Rmetrics Association and Finance Online, Zurich.
1 2 3 4 5 6 7 8 9 10 11 12 13 14  ## LPP 
# Load Swiss Pension Fund Data:
LPP < LPP2005REC
colnames(LPP)
## assetsSelect 
# Hierarchical Clustering:
hclust < assetsSelect(LPP, "hclust")
plot(hclust)
## assetsSelect 
# kmeans Clustering:
assetsSelect(LPP, "kmeans", control =
c(centers = 3, algorithm = "HartiganWong"))

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