WG | R Documentation |
The Weibull Geometric distribution
WG(mu.link = "log", sigma.link = "log", nu.link = "logit")
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 weibull geometric distribution with parameters mu
,
sigma
and nu
has density given by
f(x) = (\sigma \mu^\sigma (1-\nu) x^(\sigma - 1) \exp(-(\mu x)^\sigma))
(1- \nu \exp(-(\mu x)^\sigma))^{-2},
for x > 0
, \mu > 0
, \sigma > 0
and 0 < \nu < 1
.
Returns a gamlss.family object which can be used to fit a WG distribution in the gamlss()
function.
Johan David Marin Benjumea, johand.marin@udea.edu.co
barreto2011weibullRelDists
dWG
# Example 1
# Generating some random values with
# known mu, sigma and nu
y <- rWG(n=100, mu = 0.9, sigma = 2, nu = 0.5)
# Fitting the model
require(gamlss)
mod <- gamlss(y~1, sigma.fo=~1, nu.fo=~1, family='WG',
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(- 0.2 * x1)
sigma <- exp(1.2 - 1 * x2)
nu <- 0.5
x <- rWG(n=n, mu, sigma, nu)
mod <- gamlss(x~x1, mu.fo=~x1, sigma.fo=~x2, nu.fo=~1, family=WG,
control=gamlss.control(n.cyc=50000, trace=FALSE))
coef(mod, what="mu")
coef(mod, what="sigma")
coef(mod, what='nu')
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