dIW | R Documentation |
Density, distribution function, quantile function,
random generation and hazard function for the inverse weibull distribution with
parameters mu
and sigma
.
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)
x, q |
vector of quantiles. |
mu |
scale parameter. |
sigma |
shape parameters. |
log, log.p |
logical; if TRUE, probabilities p are given as log(p). |
lower.tail |
logical; if TRUE (default), probabilities are P[X <= x], otherwise, P[X > x]. |
p |
vector of probabilities. |
n |
number of observations. |
The inverse weibull distribution with parameters mu
and
sigma
has density given by
f(x) = μ σ x^{-σ-1} \exp(μ x^{-σ})
for x > 0, μ > 0 and σ > 0
dIW
gives the density, pIW
gives the distribution
function, qIW
gives the quantile function, rIW
generates random deviates and hIW
gives the hazard function.
Johan David Marin Benjumea, johand.marin@udea.edu.co
almalki2014modificationsRelDists
\insertRefdrapella1993complementaryRelDists
old_par <- par(mfrow = c(1, 1)) # save previous graphical parameters ## The probability density function curve(dIW(x, mu=5, sigma=2.5), from=0, to=10, ylim=c(0, 0.55), col="red", las=1, ylab="f(x)") #' ## The cumulative distribution and the Reliability function par(mfrow=c(1, 2)) curve(pIW(x, mu=5, sigma=2.5), from=0, to=10, col="red", las=1, ylab="F(x)") curve(pIW(x, mu=5, sigma=2.5, lower.tail=FALSE), from=0, to=10, col="red", las=1, ylab="R(x)") ## The quantile function p <- seq(from=0, to=0.99999, length.out=100) plot(x=qIW(p, mu=5, sigma=2.5), y=p, xlab="Quantile", las=1, ylab="Probability") curve(pIW(x, mu=5, sigma=2.5), from=0, add=TRUE, col="red") ## The random function hist(rIW(n=10000, mu=5, sigma=2.5), freq=FALSE, xlim=c(0,60), xlab="x", las=1, main="") curve(dIW(x, mu=5, sigma=2.5), from=0, add=TRUE, col="red") ## The Hazard function par(mfrow=c(1,1)) curve(hIW(x, mu=5, sigma=2.5), from=0, to=15, ylim=c(0, 0.9), col="red", ylab="Hazard function", las=1) par(old_par) # restore previous graphical parameters
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