GGD | R Documentation |
The Generalized Gompertz family
GGD(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 Generalized Gompertz Distribution with parameters mu
,
sigma
and nu
has density given by
f(x)= ν μ \exp(-\frac{μ}{σ}(\exp(σ x - 1))) (1 - \exp(-\frac{μ}{σ}(\exp(σ x - 1))))^{(ν - 1)} ,
for x ≥q 0, μ > 0, σ ≥q 0 and ν > 0
Returns a gamlss.family object which can be used to fit a GGD distribution in the gamlss()
function.
.
Johan David Marin Benjumea, johand.marin@udea.edu.co
el2013generalizedRelDists
dGGD
#Example 1 # Generating some random values with # known mu, sigma, nu and tau y <- rGGD(n=1000, mu=1, sigma=0.3, nu=1.5) # Fitting the model require(gamlss) mod <- gamlss(y~1, sigma.fo=~1, nu.fo=~1, family='GGD', 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, min=0.4, max=0.6) x2 <- runif(n, min=0.4, max=0.6) mu <- exp(0.5 - x1) sigma <- exp(-1 - x2) nu <- 1.5 x <- rGGD(n=n, mu, sigma, nu) mod <- gamlss(x~x1, sigma.fo=~x2, nu.fo=~1, family=GGD, control=gamlss.control(n.cyc=5000, trace=FALSE)) coef(mod, what="mu") coef(mod, what="sigma") exp(coef(mod, what="nu"))
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.