| triplot {klaR} | R Documentation | 
Barycentric plots
Description
Function to produce triangular (barycentric) plots illustrating proportions of 3 components, e.g. discrete 3D-distributions or mixture fractions that sum up to 1.
Usage
triplot(x = NULL, y = NULL, z = NULL, main = "", frame = TRUE, 
    label = 1:3, grid = seq(0.1, 0.9, by = 0.1), center = FALSE, 
    set.par = TRUE, ...)
Arguments
x | 
 Vector of fractions of first component
OR 3-column matrix containing all three components (omitting   | 
y | 
 (Optional) vector of fractions of second component.  | 
z | 
 (Optional) vector of fractions of third component.  | 
main | 
 Main title  | 
frame | 
 Controls whether a frame (triangle) and labels are drawn.  | 
label | 
 (Character) vector of labels for the three corners.  | 
grid | 
 Values along which grid lines are to be drawn (or   | 
center | 
 Controls whether or not to draw centerlines at which there is a 
‘tie’ between any two dimensions (see also   | 
set.par | 
 Controls whether graphical parameter   | 
... | 
 Further graphical parameters passed to   | 
Details
The barycentric plot illustrates the set of points (x,y,z) with x,y,z between 0 and 1 and x+y+z=1; that is, the triangle spanned by (1,0,0), (0,1,0) and (0,0,1) in 3-dimensional space. The three dimensions x, y and z correspond to lower left, upper and lower right corner of the plot. The greater the share of x in the proportion, the closer the point is to the lower left corner; Points on the opposite (upper right) side have a zero x-fraction. The grid lines show the points at which one dimension is held constant, horizontal lines for example contain points with a constant second dimension.
Author(s)
Christian Röver, roever@statistik.tu-dortmund.de
See Also
tripoints, trilines, triperplines, trigrid, 
triframe for points, lines and layout, tritrafo for placing labels,
and quadplot for the same in 4 dimensions.
Examples
# illustrating probabilities: 
triplot(label = c("1, 2 or 3", "4 or 5", "6"), 
    main = "die rolls: probabilities", pch = 17)
triperplines(1/2, 1/3, 1/6)
# expected... 
triplot(1/2, 1/3, 1/6, label = c("1, 2 or 3", "4 or 5", "6"), 
    main = "die rolls: expected and observed frequencies", pch = 17)
# ... and observed frequencies. 
dierolls <- matrix(sample(1:3, size = 50*20, prob = c(1/2, 1/3, 1/6), 
                          replace = TRUE), ncol = 50)
frequencies <- t(apply(dierolls, 1, 
    function(x)(summary(factor(x, levels = 1:3)))) / 50)
tripoints(frequencies)
# LDA classification posterior: 
data(iris)
require(MASS)
pred <- predict(lda(Species ~ ., data = iris),iris)
plotchar <- rep(1,150)
plotchar[pred$class != iris$Species] <- 19
triplot(pred$posterior, label = colnames(pred$posterior), 
        main = "LDA posterior assignments", center = TRUE, 
        pch = plotchar, col = rep(c("blue", "green3", "red"), rep(50, 3)), 
        grid = TRUE)
legend(x = -0.6, y = 0.7, col = c("blue", "green3", "red"), 
    pch = 15, legend = colnames(pred$posterior))