SZMW | R Documentation |
The Sarhan and Zaindin's Modified Weibull distribution
SZMW(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 Sarhan and Zaindin's Modified Weibull distribution with parameters mu
,
sigma
and nu
has density given by
f(x)=(\mu + \sigma \nu x^(\nu - 1)) \exp(- \mu x - \sigma x^\nu),
for x > 0
, \mu > 0
, \sigma > 0
and \nu > 0
.
Returns a gamlss.family object which can be used to fit a SZMW distribution in the gamlss()
function.
Johan David Marin Benjumea, johand.marin@udea.edu.co
almalki2014modificationsRelDists
\insertRefsarhan2009modifiedRelDists
dSZMW
# Example 1
# Generating some random values with
# known mu, sigma and nu
y <- rSZMW(n=100, mu = 1, sigma = 1, nu = 1.5)
# Fitting the model
require(gamlss)
mod <- gamlss(y~1, sigma.fo=~1, nu.fo=~1, family='SZMW',
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)
x2 <- runif(n)
mu <- exp(-1.6 * x1)
sigma <- exp(0.9 - 1 * x2)
nu <- 1.5
x <- rSZMW(n=n, mu, sigma, nu)
mod <- gamlss(x~x1, mu.fo=~x1, sigma.fo=~x2, nu.fo=~1, family=SZMW,
control=gamlss.control(n.cyc=50000, trace=FALSE))
coef(mod, what="mu")
coef(mod, what="sigma")
coef(mod, what='nu')
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