ternaryDiag: Ternary diagram

In robCompositions: Compositional Data Analysis

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),
  text = NULL,
  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
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., par()

Details

The relative proportions of each variable are plotted.

Author(s)

Peter Filzmoser <[e-mail]>, Matthias Templ <[e-mail]>

References

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

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)

robCompositions documentation built on Aug. 25, 2023, 5:13 p.m.