WGEE | R Documentation |
The Weigted Generalized Exponential-Exponential family
WGEE(mu.link = "log", sigma.link = "log", nu.link = "log")
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. |
The Weigted Generalized Exponential-Exponential distribution with parameters mu
,
sigma
and nu
has density given by
f(x)= \sigma \nu \exp(-\nu x) (1 - \exp(-\nu x))^{\sigma - 1} (1 - \exp(-\mu \nu x)) / 1 - \sigma B(\mu + 1, \sigma),
for x > 0
, \mu > 0
, \sigma > 0
and \nu > 0
.
Returns a gamlss.family object which can be used to fit a WGEE distribution in the gamlss()
function.
Johan David Marin Benjumea, johand.marin@udea.edu.co
mahdavi2015twoRelDists
dWGEE
# Example 1
# Generating some random values with
# known mu, sigma and nu
y <- rWGEE(n=1000, mu = 5, sigma = 0.5, nu = 1)
# Fitting the model
require(gamlss)
mod <- gamlss(y~1, sigma.fo=~1, nu.fo=~1, family='WGEE',
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 <- 500
x1 <- runif(n, min=0.4, max=0.6)
x2 <- runif(n, min=0.4, max=0.6)
mu <- exp(2 - x1)
sigma <- exp(1 - 3*x2)
nu <- 1
x <- rWGEE(n=n, mu, sigma, nu)
mod <- gamlss(x~x1, sigma.fo=~x2, nu.fo=~1, family=WGEE,
control=gamlss.control(n.cyc=50000, trace=FALSE))
coef(mod, what="mu")
coef(mod, what="sigma")
exp(coef(mod, what="nu"))
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