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)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.