# Example 1
# Generating some random values with
# known mu and sigma
y <- rPL(n=100, mu=1.5, sigma=0.2)
# Fitting the model
require(gamlss)
mod <- gamlss(y~1, sigma.fo=~1, family= 'PL',
control=gamlss.control(n.cyc=5000, trace=FALSE))
# Extracting the fitted values for mu and sigma
# using the inverse link function
exp(coef(mod, 'mu'))
exp(coef(mod, 'sigma'))
# Example 2
# Generating random values under some model
n <- 200
x1 <- runif(n, min=0.4, max=0.6)
x2 <- runif(n, min=0.4, max=0.6)
mu <- exp(1.2 - 2 * x1)
sigma <- exp(0.8 - 3 * x2)
x <- rPL(n=n, mu, sigma)
mod <- gamlss(x~x1, sigma.fo=~x2, family=PL,
control=gamlss.control(n.cyc=5000, trace=FALSE))
coef(mod, what="mu")
coef(mod, what="sigma")
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