mlegbstc {gbs} | R Documentation |
The function mlegbstc gives the maximum likelihood estimates (MLE) of the parameters α and β of the GBSD generated from the t kernel based on a type II censored sample.
mlegbstc(x, nuFixed = 2.0, status)
x |
Vector of observations. |
nuFixed |
Shape parameter corresponding to the degrees of freedom of the t distribution, which must be fixed. |
status |
Vector indicating if the observation is uncensored taking a value equal to one (1) or censored taking a value equal to zero (0). |
The MLEs of the parameters α and β of the GBSD generated from the t kernel, must be obtained using numerical procedure already implmented in {R}. In this procedure, the parameter nu is obtained by using an optimal methodology based on the data.
{mlegbstc()} computes MLEs for the parameters of the GBSD generated from the t kernel with censored data giving results according to the following list:
alphaEstimate |
Returns the value of the MLE of alpha. |
betaEstimate |
Returns the value of the MLE of beta. |
nuOptimal |
Returns the optimal value for nu. |
loglikelihood |
Returns the value of the GBSD loglikelihood. |
Barros, Michelli <michelli.karinne@gmail.com>
Leiva, Victor <victor.leiva@uv.cl, victor.leiva@yahoo.com>
Paula, Gilberto A. <giapaula@ime.usp.br>
Diaz-Garcia, J.A., Leiva, V. (2005) A new family of life distributions based on elliptically contoured distributions. J. Stat. Plan. Infer. 128:445-457 (Erratum: J. Stat. Plan. Infer. 137:1512-1513).
Leiva, V., Barros, M., Paula, G.A., Sanhueza, A. (2008) Generalized Birnbaum-Saunders distributions applied to air pollutant concentration. Environmetrics 19:235-249.
Sanhueza, A., Leiva, V., Balakrishnan, N. (2008) The generalized Birnbaum-Saunders distribution and its theory, methodology and application. Comm. Stat. Theory and Meth. 37:645-670.
## Generates a sample from the GBSD with t kernel x <- rgbs(300, alpha = 1.0, beta = 1.0, nu = 5, kernel = "t") ## Computes the likelihood for a sample x from the GBSD with t kernel ## with censored data pc <- 20 status <- c(rep(1, floor((length(x) - pc) * (length(x)) / 100)), rep(0, (floor(pc * (length(x)) / 100)))) mlegbstc(x, 2, status)