timeSeries (version 280.75)

orderColnames: Reorder Column Names of a Time Series

Description

Functions and methods dealing with the rearrangement of column names of 'timeSeries' objects. ll{ 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

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, 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.

Value

• returns a vector of character string, the rearranged column names.

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.

Examples

## data -
   MSFT = as.timeSeries(data(msft.dat))
   colnames(MSFT) = abbreviate(colnames(MSFT), 2)

## sortColnames -
   # Sort alphabetically
   sortColnames(MSFT)
  
## hclustColnames -
   head(MSFT[, hclustColnames(MSFT)])