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The Generalized Inverse Weibull family

Usage

GIW(mu.link = "log", sigma.link = "log", nu.link = "log")

Arguments

defines the mu.link, with "log" link as the default for the mu parameter.

defines the sigma.link, with "log" link as the default for the sigma.

defines the nu.link, with "log" link as the default for the nu parameter.

Value

Returns a gamlss.family object which can be used to fit a GIW distribution in the gamlss() function.

Details

The Generalized Inverse Weibull distribution with parameters mu, sigma and nu has density given by

\(f(x) = \nu \sigma \mu^{\sigma} x^{-(\sigma + 1)} exp \{-\nu (\frac{\mu}{x})^{\sigma}\},\)

for x > 0.

References

Almalki, S. J., & Nadarajah, S. (2014). Modifications of the Weibull distribution: A review. Reliability Engineering & System Safety, 124, 32-55.

De Gusmao, F. R., Ortega, E. M., & Cordeiro, G. M. (2011). The generalized inverse Weibull distribution. Statistical Papers, 52, 591-619.

See also

Author

Amylkar Urrea Montoya, amylkar.urrea@udea.edu.co

Examples

# Example 1
# Generating some random values with
# known mu, sigma and nu
y <- rGIW(n=200, mu=3, sigma=5, nu=0.5)

# Fitting the model
require(gamlss)

mod <- gamlss(y~1, sigma.fo=~1, nu.fo=~1, family='GIW',
              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'))
#> (Intercept) 
#>    2.856589 
exp(coef(mod, what='sigma'))
#> (Intercept) 
#>     4.95933 
exp(coef(mod, what='nu'))
#> (Intercept) 
#>   0.6515828 

# Example 2
# Generating random values under some model
n <- 500
x1 <- runif(n, min=0.4, max=0.6)
x2 <- runif(n, min=0.4, max=0.6)
mu <- exp(-1.02 + 3 * x1)
sigma <- exp(1.69 - 2 * x2)
nu <- 0.5
x <- rGIW(n=n, mu, sigma, nu)

mod <- gamlss(x~x1, sigma.fo=~x2, nu.fo=~1, family=GIW,
              control=gamlss.control(n.cyc=5000, trace=FALSE))

coef(mod, what="mu")
#> (Intercept)          x1 
#>  -0.9507364   2.7995149 
coef(mod, what="sigma")
#> (Intercept)          x2 
#>    1.482412   -1.540473 
exp(coef(mod, what="nu"))
#> (Intercept) 
#>   0.5268569