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.
tau.link: defines the tau.link, with "log" link as the default for the tau parameter.
Returns
Returns a gamlss.family object which can be used to fit a AddW distribution in the gamlss() function.
Details
Additive Weibull distribution with parameters mu, sigma, nu and tau has density given by
f(x)=(μνxν−1+στxτ−1)exp(−μxν−σxτ),
for x > 0.
Examples
# Example 1# Generating some random values with# known mu, sigma, nu and tau# Will not be run this example because high number is cycles# is needed in order to get good estimates## Not run:y <- rAddW(n=100, mu=1.5, sigma=0.2, nu=3, tau=0.8)# Fitting the modelrequire(gamlss)mod <- gamlss(y~1, sigma.fo=~1, nu.fo=~1, tau.fo=~1, family='AddW', control=gamlss.control(n.cyc=5000, trace=FALSE))# Extracting the fitted values for mu, sigma, nu and tau# using the inverse link functionexp(coef(mod, what='mu'))exp(coef(mod, what='sigma'))exp(coef(mod, what='nu'))exp(coef(mod, what='tau'))## End(Not run)# Example 2# Generating random values under some model# Will not be run this example because high number is cycles# is needed in order to get good estimates## Not run:n <-200x1 <- runif(n, min=0.4, max=0.6)x2 <- runif(n, min=0.4, max=0.6)mu <- exp(1.67+-3* x1)sigma <- exp(0.69-2* x2)nu <-3tau <-0.8x <- rAddW(n=n, mu, sigma, nu, tau)mod <- gamlss(x~x1, sigma.fo=~x2, nu.fo=~1, tau.fo=~1, family=AddW, control=gamlss.control(n.cyc=5000, trace=FALSE))coef(mod, what="mu")coef(mod, what="sigma")exp(coef(mod, what="nu"))exp(coef(mod, what="tau"))## End(Not run)