EGG | R Documentation |
The four parameter Exponentiated Generalized Gamma distribution
EGG(mu.link = "log", sigma.link = "log", nu.link = "log", tau.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. |
tau.link |
defines the tau.link, with "log" link as the default for the tau parameter. |
Four parameter Exponentiated Generalized Gamma distribution with parameters mu
,
sigma
, nu
and tau
has density given by
f(x) = \frac{ν σ}{μ Γ(τ)} ≤ft(\frac{x}{μ}\right)^{σ τ -1} \exp≤ft\{ - ≤ft( \frac{x}{μ} \right)^σ \right\} ≤ft\{ γ_1≤ft( τ, ≤ft( \frac{x}{μ} \right)^σ \right) \right\}^{ν-1} ,
for x > 0.
Returns a gamlss.family object which can be used to fit a EGG distribution in the gamlss()
function.
Amylkar Urrea Montoya, amylkar.urrea@udea.edu.co
almalki2014modificationsRelDists
\insertRefcordeiro2011RelDists
dEGG
# Example 1 # Generating some random values with # known mu, sigma, nu and tau y <- rEGG(n=500, mu=0.1, sigma=0.8, nu=10, tau=1.5) # Fitting the model require(gamlss) mod <- gamlss(y~1, sigma.fo=~1, nu.fo=~1, tau.fo=~1, family='EGG', control=gamlss.control(n.cyc=500, trace=FALSE)) # Extracting the fitted values for mu, sigma, nu and tau # using the inverse link function exp(coef(mod, what='mu')) exp(coef(mod, what='sigma')) exp(coef(mod, what='nu')) exp(coef(mod, what='tau')) # Example 2 # Generating random values under some model n <- 200 x1 <- runif(n, min=0.2, max=0.8) x2 <- runif(n, min=0.2, max=0.8) mu <- exp(-0.8 + -3 * x1) sigma <- exp(0.77 - 2 * x2) nu <- 10 tau <- 1.5 y <- rEGG(n=n, mu, sigma, nu, tau) mod <- gamlss(y~x1, sigma.fo=~x2, nu.fo=~1, tau.fo=~1, family=EGG, control=gamlss.control(n.cyc=500, trace=FALSE)) coef(mod, what="mu") coef(mod, what="sigma") exp(coef(mod, what="nu")) exp(coef(mod, what="tau"))
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