Functions and methods dealing with the rearrangement
of column names of 'timeSeries' objects.
orderColnames | Returns ordered column names of a time Series, |
sortColnames | Returns sorted column names of a time Series, |
sampleColnames | Returns sampled column names of a time Series, |
statsColnames | Returns statistically rearranged column names, |
pcaColnames | Returns PCA correlation ordered column names, |
hclustColnames | Returns hierarchical clustered column names. |
orderColnames(x, ...)
sortColnames(x, ...)
sampleColnames(x, ...)
statsColnames(x, FUN = colMeans, ...)
pcaColnames(x, robust = FALSE, ...)
hclustColnames(x, method = c("euclidean", "complete"), ...)
for orderColnames
, an integer vector representing the
permutaion that will sort the column names,
for the other functions, a character vector giving the rearranged column names
an object of class timesSeries
or any other rectangular
object which can be transformed by the function as.matrix
into a numeric matrix.
a character string indicating which statistical function should be applied. By default statistical ordering operates on the column means of the time series.
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
.
a logical flag which indicates if robust correlations should be used.
further arguments to be passed to the underlying functions doing the main work, see section ‘Details’.
These functions reorder the column names of a "timeSeries"
object according to some statistical measure.
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 help page
colStats
but custom functions can be used that 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.
## 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)])
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