shape
and scale
.
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)
length(n) > 1
, the length
is taken to be the number required.dweibull
gives the density,
pweibull
gives the distribution function,
qweibull
gives the quantile function, and
rweibull
generates random deviates.Invalid arguments will result in return value NaN
, with a warning.The length of the result is determined by n
for
rweibull
, and is the maximum of the lengths of the
numerical arguments for the other functions.The numerical arguments other than n
are recycled to the
length of the result. Only the first elements of the logical
arguments are used.
[dpq]weibull
are calculated directly from the definitions.
rweibull
uses inversion.shape
parameter $a$ and
scale
parameter $b$ has density given by
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.tail = FALSE, log.p = TRUE),
-(x/pi)^2.5, tolerance = 1e-15)
all.equal(qweibull(x/11, shape = 1, scale = pi), qexp(x/11, rate = 1/pi))
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