a character string indicating which statistical function
should be applied. By default statistical ordering operates
on the column means of the time series.
method
a character string with two elements. The first determines
the choice of the distance measure, see dist, and the
second determines the choice of the agglomeration method, see
hclust.
robust
a logical flag which indicates if robust correlations
should be used.
x
an object of class timesSeries or any other rectangular
object which can be transformed by the function as.matrix
into a numeric matrix.
...
further arguments to be passed, see details.
Details
Statistically Motivated Rearrangement
The function statsColnames rearranges the column names
according to a statical measure. These measure must operate on the
columns of the time series and return a vector of values which
can be sorted. Typical functions ar those listed in in help
page colStats but one can also crete his own
functions which compute for example risk or any other statistical
measure. The ... argument allows to pass additional
arguments to the underlying function FUN.
PCA Ordering of the Correlation Matrix
The function pcaColnames rearranges the column names
according to the PCA ordered correlation matrix. The argument
robust allsows to select between the use of the standard
cor and computation of robust correlations using
the function covMcd from contributed R package
robustbase. The ... argument allows to pass
additional arguments to the two underlying functions cor
or covMcd. E.g. adding method="kendall"
to the argument list calculates Kendall's rank correlations
instead the default which calculates Person's correlations.
Ordering by Hierarchical Clustering
The function pcaColnames uses the hierarchical clustering
approach hclust to rearrange the column names of the
time series.
Value
returns a vector of character string, the rearranged column names.
Examples
## Load Swiss Pension Fund Benchmark Data -
data <- LPP2005REC[,1:6]
## Abbreviate Column Names -
colnames(data)
## Sort Alphabetically -
sortColnames(data)
## Sort by Column Names by Hierarchical Clustering -
hclustColnames(data)
head(data[, hclustColnames(data)])