| cdfwei | R Documentation | 
Distribution function and quantile function of the Weibull distribution.
cdfwei(x, para = c(0, 1, 1))
quawei(f, para = c(0, 1, 1))
| x | Vector of quantiles. | 
| f | Vector of probabilities. | 
| para | Numeric vector containing the parameters of the distribution,
in the order  | 
The Weibull distribution with
location parameter \zeta,
scale parameter \beta and
shape parameter \delta has distribution function
F(x)=1-\exp[-\lbrace(x-\zeta)/\beta\rbrace^\delta]
for x>\zeta.
cdfwei gives the distribution function;
quawei gives the quantile function.
The functions expect the distribution parameters in a vector,
rather than as separate arguments as in the standard R
distribution functions pnorm, qnorm, etc.
cdfgev for the generalized extreme-value distribution,
of which the Weibull (reflected through the origin) is a special case.
# Random sample from a 2-parameter Weibull distribution
# with scale parameter 2 and shape parameter 1.5.
quawei(runif(100), c(0,2,1.5))
# Illustrate the relation between Weibull and GEV distributions.
# weifit() fits a Weibull distribution to data and returns
#   quantiles of the fitted distribution
# gevfit() fits a Weibull distribution as a "reverse GEV",
#   i.e. fits a GEV distribution to the negated data,
#   then computes negated quantiles
weifit <- function(qval, x) quawei(qval, pelwei(samlmu(x)))
gevfit <- function(qval, x) -quagev(1-qval, pelgev(samlmu(-x)))
# Compare on Ozone data
data(airquality)
weifit(c(0.2,0.5,0.8), airquality$Ozone)
gevfit(c(0.2,0.5,0.8), airquality$Ozone)
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