Compositional (version 4.3)

Ternary diagram: Ternary diagram

Description

Ternary diagram.

Usage

ternary(x, means = TRUE, pca = FALSE, colour = NULL)

Arguments

x

A matrix with the compositional data.

means

A boolean variable. Should the closed geometric mean and the arithmetic mean appear (TRUE) or not (FALSE)?.

pca

Should the first PCA calculated Aitchison (1983) described appear? If yes, then this should be TRUE, or FALSE otherwise.

colour

If you want the points to appear in different colour put a vector with the colour numbers or colours.

Value

The ternary plot and a 2-row matrix with the means. The closed geometric and the simple arithmetic mean vector and or the first principcal component will appear as well if the user has asked for them.

Details

The first PCA is calcualte using the centred log-ratio transformation as Aitchison (1983, 1986) suggested. If the data contain zero values, the first PCA will not be plotted. There are two ways to create a ternary graph. The one I used here, where each edge is equal to 1 and the one Aitchison (1986) uses. For every given point, the sum of the distances from the edges is equal to 1. Zeros in the data appear with green circles in the triangle and you will also see NaN in the closed geometric mean.

References

Aitchison, J. (1983). Principal component analysis of compositional data. Biometrika 70(1):57-65.

Aitchison J. (1986). The statistical analysis of compositional data. Chapman \& Hall.

See Also

comp.den, alfa, diri.contour, comp.kerncontour

Examples

# NOT RUN {
x <- as.matrix(iris[, 1:3])
x <- x / rowSums(x)
ternary(x, means = TRUE, pca = TRUE)
# }