variation {compositions} | R Documentation |

## Variation matrices of amounts and compositions

### Description

Compute the variation matrix in the various approaches of compositional and amount data analysis. Pay attention that this is not computing the variance or covariance matrix!

### Usage

```
variation(x,...)
## S3 method for class 'acomp'
variation(x, ...,robust=getOption("robust"))
## S3 method for class 'rcomp'
variation(x, ...,robust=getOption("robust"))
## S3 method for class 'aplus'
variation(x, ...,robust=getOption("robust"))
## S3 method for class 'rplus'
variation(x, ...,robust=getOption("robust"))
## S3 method for class 'rmult'
variation(x, ...,robust=getOption("robust"))
is.variation(M, tol=1e-10)
```

### Arguments

`x` |
a dataset, eventually of amounts or compositions |

`...` |
currently unused |

`robust` |
A description of a robust estimator. FALSE for the classical estimators. See robustnessInCompositions for further details. |

`M` |
a matrix, to check if it is a valid variation |

`tol` |
tolerance for the check |

### Details

The variation matrix was defined in the `acomp`

context of
analysis of compositions as the matrix of variances of all
possible log-ratios among components (Aitchison, 1986). The
generalization to rcomp objects is simply to reproduce the
variance of all possible differences between components. The
amount (`aplus`

, `rplus`

) and rmult objects
should not be treated with variation
matrices, because this was intended to skip the existence of a closure
(which does not exist in the case of amounts).

### Value

The variation matrix of x.

For `is.variation`

, a boolean saying if the matrix satisfies the conditions to be a variation matrix.

### Author(s)

K.Gerald v.d. Boogaart http://www.stat.boogaart.de

### See Also

`cdt`

, `clrvar2ilr`

, `clo`

,
`mean.acomp`

, `acomp`

, `rcomp`

,
`aplus`

, `rplus`

### Examples

```
data(SimulatedAmounts)
meanCol(sa.lognormals)
variation(acomp(sa.lognormals))
variation(rcomp(sa.lognormals))
variation(aplus(sa.lognormals))
variation(rplus(sa.lognormals))
variation(rmult(sa.lognormals))
```

*compositions*version 2.0-8 Index]