mlebs {bibs} | R Documentation |
Computing the maximum likelihood (ML) estimator for the generalized Birnbaum-Saunders (GBS) distribution.
Description
Computing the ML estimator for the GBS distribution proposed by Owen (2006) whose density function is given by
where . The parameters of GBS distribution are
,
, and
. For
, the GBS distribution turns into the ordinary Birnbaum-Saunders distribution.
Usage
mlebs(x, start, method = "Nelder-Mead", CI = 0.95)
Arguments
x |
Vector of observations. |
start |
Vector of the initial values. |
method |
The method for the numerically optimization that includes one of |
CI |
Confidence level for constructing asymptotic confidence intervals. That is 0.95 by default. |
Value
A list including the ML estimator, goodness-of-fit measures, asymptotic confidence interval (CI) and corresponding standard errors, and Fisher information matix.
Author(s)
Mahdi Teimouri
Examples
data(fatigue)
x <- fatigue
mlebs(x, start = c(1, 29), method = "Nelder-Mead", CI = 0.95)
[Package bibs version 1.1.1 Index]