Compositional (version 4.1)

Estimation of the value of alpha in the folded model: Estimation of the value of \(\alpha\) in the folded model

Description

Estimation of the value of \(\alpha\) in the folded model.

Usage

a.est(x)

Arguments

x

A matrix with the compositional data. No zero vaues are allowed.

Value

A list including:

runtime

The runtime of the algorithm.

best

The estimated optimal \(\alpha\) of the folded model.

loglik

The maximimised log-likelihood of the folded model.

p

The estimated probability inside the simplex of the folded model.

mu

The estimated mean vector of the folded model.

su

The estimated covariance matrix of the folded model.

Details

This is a function for choosing or estimating the value of \(\alpha\) in the folded model (Tsagris and Stewart, 2019).

References

Tsagris Michail and Stewart Connie, (2020). A folded model for compositional data analysis. Australian and New Zealand Journal of Statistics (to appear). https://arxiv.org/pdf/1802.07330.pdf

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

alfa.profile, alfa, alfainv, alpha.mle

Examples

# NOT RUN {
x <- as.matrix(iris[, 1:4])
x <- x / rowSums(x)
alfa.tune(x)
a.est(x)
# }