| ternaryDiag {robCompositions} | 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> http://www.statistik.tuwien.ac.at/public/filz/, Matthias Templ
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.
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)