Reorder column names of a time series
statisticsorderColnames.Rd
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. 
Usage
orderColnames(x, ...)
sortColnames(x, ...)
sampleColnames(x, ...)
statsColnames(x, FUN = colMeans, ...)
pcaColnames(x, robust = FALSE, ...)
hclustColnames(x, method = c("euclidean", "complete"), ...)
Arguments
 x

an object of class
timesSeries
or any other rectangular object which can be transformed by the functionas.matrix
into a numeric matrix.  FUN

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, seehclust
.  robust

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’.
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.
Value
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
Examples
## Load Swiss Pension Fund Benchmark Data 
data < LPP2005REC[,1:6]
## Abbreviate Column Names 
colnames(data)
#> [1] "SBI" "SPI" "SII" "LMI" "MPI" "ALT"
## Sort Alphabetically 
sortColnames(data)
#> [1] "ALT" "LMI" "MPI" "SBI" "SII" "SPI"
## Sort by Column Names by Hierarchical Clustering 
hclustColnames(data)
#> [1] "SII" "SBI" "LMI" "SPI" "MPI" "ALT"
head(data[, hclustColnames(data)])
#> GMT
#> SII SBI LMI SPI MPI
#> 20051101 0.003190926 0.000612745 0.001108882 0.008414595 0.001548062
#> 20051102 0.004117638 0.002762009 0.001175939 0.002519342 0.000342876
#> 20051103 0.005209409 0.001153092 0.000992456 0.012707292 0.010502959
#> 20051104 0.001127165 0.003235750 0.001198528 0.000702757 0.011679558
#> 20051107 0.001795839 0.001310970 0.000360366 0.006205226 0.002709618
#> 20051108 0.002103374 0.000539312 0.002327040 0.000329260 0.000346843
#> ALT
#> 20051101 0.002572971
#> 20051102 0.001141604
#> 20051103 0.005007442
#> 20051104 0.009482677
#> 20051107 0.004723952
#> 20051108 0.000853619