mlfatigue: Gamma distribution maximum likelihood estimation

In univariateML: Maximum Likelihood Estimation for Univariate Densities

Gamma distribution maximum likelihood estimation

Description

Uses Newton-Raphson to estimate the parameters of the Birnbaum–Saunders distribution. The parameter mu is set to 0, hence only alpha and beta are estmated.

Usage

mlfatigue(x, na.rm = FALSE, ...)

Arguments

x	a (non-empty) numeric vector of data values.
na.rm	logical. Should missing values be removed?
...	reltol is the relative accuracy requested, defaults to .Machine$double.eps^0.25. iterlim is a positive integer specifying the maximum number of iterations to be performed before the program is terminated (defaults to 100).

Details

For the density function of the Birnbaum–Saunders distribution see BirnbaumSaunders.

Value

mlfatigue returns an object of class univariateML. This is a named numeric vector with maximum likelihood estimates for alpha and beta, with mu=0, and the following attributes:

model	The name of the model.
density	The density associated with the estimates.
logLik	The loglikelihood at the maximum.
support	The support of the density.
n	The number of observations.
call	The call as captured my match.call

References

From, S. G., & Li, L. (2006). Estimation of the parameters of the Birnbaum<U+2013>Saunders distribution. Communications in Statistics: Theory and Methods, 35(12), 2157<U+2013>2169. https://doi.org/10.1080/03610920600853563

Examples

mlfatigue(precip)

univariateML documentation built on April 3, 2025, 11:09 p.m.