orderColnames | R Documentation |

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"), ...)
```

`x` |
an object of class |

`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 |

`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’. |

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.

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

```
## 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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