cdfwei gives the distribution function; quawei gives the quantile function.
Note
The functions expect the distribution parameters in a vector, rather than as separate arguments as in the standard
distribution functions pnorm, qnorm, etc.
See Also
cdfgev for the generalized extreme-value distribution, of which the Weibull (reflected through the origin) is a special case.
Examples
# 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 quantilesweifit <-function(qval, x) quawei(qval, pelwei(samlmu(x)))gevfit <-function(qval, x)-quagev(1-qval, pelgev(samlmu(-x)))# Compare on Ozone datadata(airquality)weifit(c(0.2,0.5,0.8), airquality$Ozone)gevfit(c(0.2,0.5,0.8), airquality$Ozone)