Compositional (version 5.5)

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, cont.line = FALSE)

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.

cont.line

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

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

folded.contour, compnorm.contour, diri.contour, mix.compnorm.contour, bivt.contour, skewnorm.contour

Examples

# NOT RUN {
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)
# }