LW {RelDists}

The Log-Weibull family

Description

The Log-Weibull distribution

Usage

LW(mu.link = "identity", sigma.link = "log")

Arguments

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.

Details

The Log-Weibull Distribution with parameters mu and sigma has density given by

f(y)=(1/\sigma) e^{((y - \mu)/\sigma)} exp\{-e^{((y - \mu)/\sigma)}\},

for - infty < y < infty.

Value

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

Author(s)

Amylkar Urrea Montoya, [e-mail]

References

Almalki SJ, Nadarajah S (2014). “Modifications of the Weibull distribution: A review.” Reliability Engineering & System Safety, 124, 32–55. doi:10.1016/j.ress.2013.11.010.

E.J G (1958). Statistics of extremes. Columbia University Press. ISBN 10:0231021909.

See Also

dLW

Examples

# Example 1
# Generating some random values with
# known mu and sigma 
y <- rLW(n=100, mu=0, sigma=1.5)

# Fitting the model
require(gamlss)

mod <- gamlss(y~1, sigma.fo=~1, family= 'LW',
              control=gamlss.control(n.cyc=5000, trace=FALSE))

# Extracting the fitted values for mu and sigma
# using the inverse link function
coef(mod, 'mu')
exp(coef(mod, 'sigma'))

# 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 <- 1.5 - 3 * x1
sigma <- exp(1.4 - 2 * x2)
x <- rLW(n=n, mu, sigma)

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

coef(mod, what="mu")
coef(mod, what="sigma")