Contour plot of the normal distribution in S^2 {Compositional} | R Documentation |
Contour plot of the normal distribution in S^2.
norm.contour(m, s, type = "alr", n = 100, x = NULL, cont.line = FALSE)
m |
The mean vector. |
s |
The covariance matrix. |
type |
The type of trasformation used, either the additive log-ratio ("alr"), the isometric log-ratio ("ilr") or the pivot coordinate ("pivot") transformation. |
n |
The number of grid points to consider over which the density is calculated. |
x |
This is either NULL (no data) or contains a 3 column matrix with compositional data. |
cont.line |
Do you want the contour lines to appear? If yes, set this TRUE. |
The alr or the ilr transformation is applied to the compositional data at first. Then for a grid of points within the 2-dimensional simplex the bivariate normal density is calculated and the contours are plotted along with the points.
A ternary diagram with the points (if appear = TRUE) and the bivariate normal contour lines.
Michail Tsagris and Christos Adam.
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr and Christos Adam pada4m4@gmail.com.
diri.contour, mixnorm.contour, bivt.contour, skewnorm.contour
x <- as.matrix(iris[, 1:3]) x <- x / rowSums(x) y <- Compositional::alr(x) m <- colMeans(y) s <- cov(y) norm.contour(m, s)