Compositional (version 1.2)

alfa.tune: 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.

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.

Details

This is a faster function than alfa.profile for choosing the value of $\alpha$.

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. http://arxiv.org/pdf/1106.1451.pdf

See Also

alfa.profile, alfa, alfainv

Examples

library(MASS)
x <- iris[, 1:4]
alfa.tune(x)
alfa.profile(x)