View source: R/biplot.pcaCoDa.R

biplot.pcaCoDa | R Documentation |

Provides robust compositional biplots.

```
## S3 method for class 'pcaCoDa'
biplot(x, y, ..., choices = 1:2)
```

`x` |
object of class ‘pcaCoDa’ |

`y` |
... |

`...` |
arguments passed to plot methods |

`choices` |
selection of two principal components by number. Default: c(1,2) |

The robust compositional biplot according to Aitchison and Greenacre (2002),
computed from (robust) loadings and scores resulting from `pcaCoDa`

, is performed.

The robust compositional biplot.

M. Templ, K. Hron

Aitchison, J. and Greenacre, M. (2002). Biplots of compositional
data. *Applied Statistics*, **51**, 375-392. \

Filzmoser, P., Hron, K., Reimann, C. (2009) Principal component analysis for
compositional data with outliers. *Environmetrics*, **20** (6),
621–632.

`pcaCoDa`

, `plot.pcaCoDa`

```
data(coffee)
p1 <- pcaCoDa(coffee[,-1])
p1
plot(p1, which = 2, choices = 1:2)
# exemplarly, showing the first and third PC
a <- p1$princompOutputClr
biplot(a, choices = c(1,3))
## with labels for the scores:
data(arcticLake)
rownames(arcticLake) <- paste(sample(letters[1:26], nrow(arcticLake), replace=TRUE),
1:nrow(arcticLake), sep="")
pc <- pcaCoDa(arcticLake, method="classical")
plot(pc, xlabs=rownames(arcticLake), which = 2)
plot(pc, xlabs=rownames(arcticLake), which = 3)
```

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