MLE of the folded model for a given value of
alpha.mle(x, a)
a.mle(a, x)A matrix with the compositional data. No zero vaues are allowed.
A value of
If "alpha.mle" is called, a list including:
The nubmer of iterations the EM algorithm required.
The maximimized log-likelihood of the folded model.
The estimated probability inside the simplex of the folded model.
The estimated mean vector of the folded model.
The estimated covariance matrix of the folded model.
If "a.mle" is called, the log-likelihood is returned only.
This is a function for choosing or estimating the value of a.est.
Tsagris M. and Stewart C. (2020). A folded model for compositional data analysis. Australian and New Zealand Journal of Statistics, 62(2): 249-277. 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
# NOT RUN {
x <- as.matrix(iris[, 1:4])
x <- x / rowSums(x)
mod <- alfa.tune(x)
mod
alpha.mle(x, mod[1])
# }
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