Density, distribution function, quantile function,
random generation and hazard function for the inverse weibull distribution with
parameters mu
and sigma
.
Usage
dIW(x, mu, sigma, log = FALSE)
pIW(q, mu, sigma, lower.tail = TRUE, log.p = FALSE)
qIW(p, mu, sigma, lower.tail = TRUE, log.p = FALSE)
rIW(n, mu, sigma)
hIW(x, mu, sigma)
Value
dIW
gives the density, pIW
gives the distribution
function, qIW
gives the quantile function, rIW
generates random deviates and hIW
gives the hazard function.
Details
The inverse weibull distribution with parameters mu
and
sigma
has density given by
\(f(x) = \mu \sigma x^{-\sigma-1} \exp(-\mu x^{-\sigma})\)
for \(x > 0\), \(\mu > 0\) and \(\sigma > 0\)
Author
Freddy Hernandez, fhernanb@unal.edu.co
Examples
# The probability density function
curve(dIW(x, mu=1, sigma=2), from=0, to=10,
col="red", las=1, ylab="f(x)")
# The cumulative distribution and the Reliability function
par(mfrow=c(1, 2))
curve(pIW(x, mu=1, sigma=2),
from=0, to=10, col="red", las=1, ylab="F(x)")
curve(pIW(x, mu=1, sigma=2, lower.tail=FALSE),
from=0, to=10, col="red", las=1, ylab="R(x)")
# The quantile function
p <- seq(from=0, to=0.99, length.out=100)
plot(x=qIW(p, mu=1, sigma=2), y=p, xlab="Quantile",
las=1, ylab="Probability")
curve(pIW(x, mu=1, sigma=2), from=0, add=TRUE, col="red")
# The random function
hist(rIW(n=1000, mu=1, sigma=2), freq=FALSE, xlim=c(0, 40),
xlab="x", las=1, main="")
curve(dIW(x, mu=1, sigma=2), from=0, add=TRUE, col="red")
# The Hazard function
par(mfrow=c(1, 1))
curve(hIW(x, mu=1, sigma=2), from=0, to=15,
col="red", ylab="Hazard function", las=1)