alfa.contour: Contour plot of the alpha multivariate normal in S^2

In Compositional: Compositional Data Analysis

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 [e-mail] and Christos Adam [e-mail].

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

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)

Compositional documentation built on July 8, 2022, 1:06 a.m.