Contour plot of the alpha multivariate normal in S^2 {Compositional}R Documentation

Contour plot of the α multivariate normal in S^2

Description

Contour plot of the α multivariate normal in S^2.

Usage

alfa.contour(m, s, a, n = 100, x = NULL, cont.line = FALSE)

Arguments

m

The mean vector of the α multivariate normal model.

s

The covariance matrix of the α multivariate normal model.

a

The value of a for the α-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.

Details

The α-transformation is applied to the compositional data and then for a grid of points within the 2-dimensional simplex, the density of the α multivariate normal is calculated and the contours are plotted.

Value

The contour plot of the α multivariate normal appears.

Author(s)

Michail Tsagris and Christos Adam.

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

References

Tsagris M.T., Preston S. and Wood A.T.A. (2011). A data-based power transformation for compositional data. In Proceedings of the 4th Compositional Data Analysis Workshop, Girona, Spain. https://arxiv.org/pdf/1106.1451.pdf

See Also

fold.contour, norm.contour, diri.contour, mixnorm.contour, bivt.contour, skewnorm.contour

Examples

x <- as.matrix(iris[, 1:3])
x <- x / rowSums(x)
a <- a.est(x)$best
m <- colMeans(alfa(x, a)$aff)
s <- cov(alfa(x, a)$aff)
alfa.contour(m, s, a)

[Package Compositional version 5.2 Index]