robCompositions (version 2.0.0)

ternaryDiag: Ternary diagram

Description

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

Usage

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

Arguments

x

matrix or data.frame with 3 columns

name

names of the variables

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., par()

Details

The relative proportions of each variable are plotted.

References

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

See Also

ternary

Examples

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)