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\name{Weibull}\alias{Weibull}\alias{dweibull}\alias{pweibull}\alias{qweibull}\alias{rweibull}\title{The Weibull Distribution}\description{Density, distribution function, quantile function and randomgeneration for the Weibull distribution with parameters \code{shape}and \code{scale}.}\usage{dweibull(x, shape, scale = 1, log = FALSE)pweibull(q, shape, scale = 1, lower.tail = TRUE, log.p = FALSE)qweibull(p, shape, scale = 1, lower.tail = TRUE, log.p = FALSE)rweibull(n, shape, scale = 1)}\arguments{\item{x, q}{vector of quantiles.}\item{p}{vector of probabilities.}\item{n}{number of observations. If \code{length(n) > 1}, the lengthis taken to be the number required.}\item{shape, scale}{shape and scale parameters, the latter defaulting to 1.}\item{log, log.p}{logical; if TRUE, probabilities p are given as log(p).}\item{lower.tail}{logical; if TRUE (default), probabilities are\eqn{P[X \le x]}{P[X <= x]}, otherwise, \eqn{P[X > x]}{P[X > x]}.}}\value{\code{dweibull} gives the density,\code{pweibull} gives the distribution function,\code{qweibull} gives the quantile function, and\code{rweibull} generates random deviates.Invalid arguments will result in return value \code{NaN}, with a warning.}\details{The Weibull distribution with \code{shape} parameter \eqn{a} and\code{scale} parameter \eqn{\sigma}{b} has density given by\deqn{f(x) = (a/\sigma) {(x/\sigma)}^{a-1} \exp (-{(x/\sigma)}^{a})}{%f(x) = (a/b) (x/b)^(a-1) exp(- (x/b)^a)}for \eqn{x \ge 0}.The cumulative distribution function is\eqn{F(x) = 1 - \exp(-{(x/\sigma)}^a)}{F(x) = 1 - exp(- (x/b)^a)}on \eqn{x \ge 0}, themean is \eqn{E(X) = \sigma \Gamma(1 + 1/a)}{E(X) = b Gamma(1 + 1/a)}, andthe \eqn{Var(X) = \sigma^2(\Gamma(1 + 2/a)-(\Gamma(1 + 1/a))^2)}{%Var(X) = b^2 * (Gamma(1 + 2/a) - (Gamma(1 + 1/a))^2)}.}\note{The cumulative hazard \eqn{H(t) = - \log(1 - F(t))}{H(t) = - log(1 - F(t))}is \code{-pweibull(t, a, b, lower = FALSE, log = TRUE)} which is just\eqn{H(t) = {(t/b)}^a}.}\source{\code{[dpq]weibull} are calculated directly from the definitions.\code{rweibull} uses inversion.}\references{Johnson, N. L., Kotz, S. and Balakrishnan, N. (1995)\emph{Continuous Univariate Distributions}, volume 1, chapter 21.Wiley, New York.}\seealso{The \link{Exponential} is a special case of the Weibull distribution.}\examples{x <- c(0,rlnorm(50))all.equal(dweibull(x, shape = 1), dexp(x))all.equal(pweibull(x, shape = 1, scale = pi), pexp(x, rate = 1/pi))## Cumulative hazard H():all.equal(pweibull(x, 2.5, pi, lower=FALSE, log=TRUE), -(x/pi)^2.5,tol = 1e-15)all.equal(qweibull(x/11, shape = 1, scale = pi), qexp(x/11, rate = 1/pi))}\keyword{distribution}