Contour plot of the normal distribution in S^2
Contour plot of the normal distribution in S^2.
norm.contour(m, s, type = "alr", n = 100, x = NULL)
m |
The mean vector. |
s |
The covariance matrix. |
type |
This is either "alr" or "ilr", corresponding to the additive and the isometric log-ratio transformation respectively. |
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. |
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
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr and Giorgos Athineou <gioathineou@gmail.com>
Aitchison J. (1986). The statistical analysis of compositional data. Chapman \& Hall.
x <- as.matrix(iris[, 1:3]) x <- x / rowSums(x) y <- Compositional::alr(x) m <- colMeans(y) s <- cov(y) norm.contour(m, s)
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