EW | R Documentation |
The Exponentiated Weibull distribution
EW(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 Exponentiated Weibull Distribution with parameters mu
,
sigma
and nu
has density given by
f(x)=ν μ σ x^{σ-1} \exp(-μ x^σ) (1-\exp(-μ x^σ))^{ν-1},
for x > 0.
Returns a gamlss.family object which can be used to fit a EW distribution in the gamlss()
function.
dEW
# Example 1 # Generating some random values with # known mu, sigma and nu # Will not be run this example because high number is cycles # is needed in order to get good estimates ## Not run: y <- rEW(n=100, mu=2, sigma=1.5, nu=0.5) # Fitting the model require(gamlss) mod <- gamlss(y~1, sigma.fo=~1, nu.fo=~1, family='EW', 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')) ## 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 <- 200 x1 <- rpois(n, lambda=2) x2 <- runif(n) mu <- exp(2 + -3 * x1) sigma <- exp(3 - 2 * x2) nu <- 2 x <- rEW(n=n, mu, sigma, nu) mod <- gamlss(x~x1, sigma.fo=~x2, nu.fo=~1, family=EW, control=gamlss.control(n.cyc=5000, trace=FALSE)) coef(mod, what="mu") coef(mod, what="sigma") exp(coef(mod, what="nu")) ## End(Not run)
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