Contour plot of the kernel density estimate in S^2 {Compositional}R Documentation

Contour plot of the kernel density estimate in S^2

Description

Contour plot of the kernel density estimate in S^2.

Usage

comp.kerncontour(x, type = "alr", n = 100, cont.line = FALSE)

Arguments

x

A matrix with the compositional data. It has to be a 3 column 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.

cont.line

Do you want the contour lines to appear? If yes, set this TRUE.

Details

The alr or the ilr transformation are applied to the compositional data. Then, the optimal bandwidth using maximum likelihood cross-validation is chosen. The multivariate normal kernel density is calculated for a grid of points. Those points are the points on the 2-dimensional simplex. Finally the contours are plotted.

Value

A ternary diagram with the points and the kernel contour lines.

Author(s)

Michail Tsagris and Christos Adam.

R implementation and documentation: Michail Tsagris mtsagris@uoc.gr and Christos Adam pada4m4@gmail.com.

References

M.P. Wand and M.C. Jones (1995). Kernel smoothing, CrC Press.

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

See Also

diri.contour, mixnorm.contour, bivt.contour, norm.contour

Examples

x <- as.matrix(iris[, 1:3])
x <- x / rowSums(x)
comp.kerncontour(x, type = "alr", n = 20)
comp.kerncontour(x, type = "ilr", n = 20)

[Package Compositional version 5.2 Index]