Compositional (version 5.0)

Contour plot of the alpha multivariate normal in S^2: Contour plot of the \(\alpha\) multivariate normal in \(S^2\)

Description

Contour plot of the \(\alpha\) multivariate normal in \(S^2\).

Usage

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

Arguments

m

The mean vector of the \(\alpha\) multivariate normal model.

s

The covariance matrix of the \(\alpha\) multivariate normal model.

a

The value of a for the \(\alpha\)-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.

Value

The contour plot of the \(\alpha\) multivariate normal appears.

Details

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

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

# NOT RUN {
x <- as.matrix(iris[, 1:3])
x <- x / rowSums(x)
a <- a.est(x)$best
mod <- alpha.mle(x, a)
fold.contour(mod$mu, mod$su, mod$p, a)
# }