| 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) = (σ μ^σ (1-ν) x^(σ - 1) \exp(-(μ x)^σ)) (1- ν \exp(-(μ x)^σ))^{-2},
for x > 0, μ > 0, σ > 0 and 0 < ν < 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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