cor.acomp | R Documentation |

Computes the correlation matrix in the various approaches of compositional and amount data analysis.

```
cor(x,y=NULL,...)
## Default S3 method:
cor(x, y=NULL, use="everything",
method=c("pearson", "kendall", "spearman"),...)
## S3 method for class 'acomp'
cor(x,y=NULL,...,robust=getOption("robust"))
## S3 method for class 'rcomp'
cor(x,y=NULL,...,robust=getOption("robust"))
## S3 method for class 'aplus'
cor(x,y=NULL,...,robust=getOption("robust"))
## S3 method for class 'rplus'
cor(x,y=NULL,...,robust=getOption("robust"))
## S3 method for class 'rmult'
cor(x,y=NULL,...,robust=getOption("robust"))
```

`x` |
a data set, eventually of amounts or compositions |

`y` |
a second data set, eventually of amounts or compositions |

`use` |
see |

`method` |
see |

`...` |
further arguments to |

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

The correlation matrix does not make much sense for compositions.

In R versions older than v2.0.0, `cor`

was defined
in package “base” instead of in “stats”.
This might produce some misfunction.

The correlation matrix.

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

`var.acomp`

```
data(SimulatedAmounts)
meanCol(sa.lognormals)
cor(acomp(sa.lognormals5[,1:3]),acomp(sa.lognormals5[,4:5]))
cor(rcomp(sa.lognormals5[,1:3]),rcomp(sa.lognormals5[,4:5]))
cor(aplus(sa.lognormals5[,1:3]),aplus(sa.lognormals5[,4:5]))
cor(rplus(sa.lognormals5[,1:3]),rplus(sa.lognormals5[,4:5]))
cor(acomp(sa.lognormals5[,1:3]),aplus(sa.lognormals5[,4:5]))
```

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