ternaryDiag | R Documentation |

This plot shows the relative proportions of three variables (compositional parts) in one diagramm. Before plotting, the data are scaled.

```
ternaryDiag(
x,
name = colnames(x),
text = NULL,
grid = TRUE,
gridCol = grey(0.6),
mcex = 1.2,
line = "none",
robust = TRUE,
group = NULL,
tol = 0.975,
...
)
```

`x` |
matrix or data.frame with 3 columns |

`name` |
names of the variables |

`text` |
default NULL, text for each point can be provided |

`grid` |
if TRUE a grid is plotted additionally in the ternary diagram |

`gridCol` |
color for the grid lines |

`mcex` |
label size |

`line` |
may be set to “none”, “pca”, “regression”, “regressionconf”, “regressionpred”, “ellipse”, “lda” |

`robust` |
if line equals TRUE, it dedicates if a robust estimation is applied or not. |

`group` |
if line equals “da”, it determines the grouping variable |

`tol` |
if line equals “ellipse”, it determines the parameter for the tolerance ellipse |

`...` |
further parameters, see, e.g., |

The relative proportions of each variable are plotted.

Peter Filzmoser <P.Filzmoser@tuwien.ac.at>, Matthias Templ <matthias.templ@fhnw.ch>

Reimann, C., Filzmoser, P., Garrett, R.G., Dutter, R. (2008)
*Statistical Data Analysis Explained. Applied Environmental Statistics with
R*. John Wiley and Sons, Chichester.

```
data(arcticLake)
ternaryDiag(arcticLake)
data(coffee)
x <- coffee[,2:4]
grp <- as.integer(coffee[,1])
ternaryDiag(x, col=grp, pch=grp)
ternaryDiag(x, grid=FALSE, col=grp, pch=grp)
legend("topright", legend=unique(coffee[,4]), pch=1:2, col=1:2)
ternaryDiag(x, grid=FALSE, col=grp, pch=grp, line="ellipse", tol=c(0.975,0.9), lty=2)
ternaryDiag(x, grid=FALSE, line="pca")
ternaryDiag(x, grid=FALSE, col=grp, pch=grp, line="pca", lty=2, lwd=2)
```

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