GammaW {RelDists} | R Documentation |
The Gamma Weibull family
Description
The Gamma Weibull family
Usage
GammaW(mu.link = "log", sigma.link = "log", nu.link = "log")
Arguments
mu.link |
defines the mu.link, with "log" link as the default for the mu parameter. |
sigma.link |
defines the sigma.link, with "log" link as the default for the sigma. |
nu.link |
defines the nu.link, with "log" link as the default for the nu parameter. |
Details
The Gamma Weibull distribution with parameters mu
,
sigma
and nu
has density given by
f(x)= \frac{\sigma \mu^{\nu}}{\Gamma (\nu)} x^{\nu \sigma - 1} \exp(-\mu x^\sigma),
for x > 0
, \mu > 0
, \sigma \geq 0
and \nu > 0
.
Value
Returns a gamlss.family object which can be used to fit a GammaW distribution in the gamlss()
function.
Author(s)
Johan David Marin Benjumea, johand.marin@udea.edu.co
References
Almalki SJ, Nadarajah S (2014). “Modifications of the Weibull distribution: A review.” Reliability Engineering & System Safety, 124, 32–55. doi:10.1016/j.ress.2013.11.010.
Stacy EW, others (1962). “A generalization of the gamma distribution.” The Annals of mathematical statistics, 33(3), 1187–1192.
See Also
Examples
# Example 1
# Generating some random values with
# known mu, sigma and nu
y <- rGammaW(n=100, mu = 0.5, sigma = 2, nu=1)
# Fitting the model
require(gamlss)
mod <- gamlss(y~1, sigma.fo=~1, nu.fo=~1, family='GammaW',
control=gamlss.control(n.cyc=5000, trace=FALSE))
# Extracting the fitted values for mu, sigma and nu
# using the inverse link function
exp(coef(mod, what='mu'))
exp(coef(mod, what='sigma'))
exp(coef(mod, what='nu'))
# Example 2
# Generating random values under some model
n <- 200
x1 <- runif(n)
x2 <- runif(n)
mu <- exp(-1.6 * x1)
sigma <- exp(1.1 - 1 * x2)
nu <- 1
x <- rGammaW(n=n, mu, sigma, nu)
mod <- gamlss(x~x1, mu.fo=~x1, sigma.fo=~x2, nu.fo=~1, family=GammaW,
control=gamlss.control(n.cyc=50000, trace=FALSE))
coef(mod, what="mu")
coef(mod, what="sigma")
coef(mod, what='nu')