| Fast estimation of the value of alpha {Compositional} | R Documentation |
Fast estimation of the value of \alpha
Description
Fast estimation of the value of \alpha.
Usage
alfa.tune(x, B = 1, ncores = 1)
Arguments
x |
A matrix with the compositional data. No zero vaues are allowed. |
B |
If no (bootstrap based) confidence intervals should be returned this should be 1 and more than 1 otherwise. |
ncores |
If ncores is greater than 1 parallel computing is performed. It is advisable to use it if you have many observations and or many variables, otherwise it will slow down th process. |
Details
This is a faster function than alfa.profile for choosing the value of \alpha.
Value
A vector with the best alpha, the maximised log-likelihood and the log-likelihood at \alpha=0, when B = 1 (no bootstrap). If B>1 a list including:
param |
The best alpha and the value of the log-likelihod, along with the 95% bootstrap based confidence intervals. |
message |
A message with some information about the histogram. |
runtime |
The time (in seconds) of the process. |
Author(s)
Michail Tsagris.
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr and Giorgos Athineou <gioathineou@gmail.com>.
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
Examples
library(MASS)
x <- as.matrix(iris[, 1:4])
x <- x / rowSums(x)
alfa.tune(x)
alfa.profile(x)