statistics-orderColnames: Reorder Column Names of a Time Series In timeSeries: Financial Time Series Objects (Rmetrics)

Description

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

 ```1 2 3 4 5 6``` ```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.

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

 ``` 1 2 3 4 5 6 7 8 9 10 11 12``` ```## 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)]) ```

timeSeries documentation built on Jan. 25, 2020, 1:07 a.m.