rweibull | R Documentation |
Density function, distribution function, quantile function and random generation for the reverse (or negative) Weibull distribution with location, scale and shape parameters.
drweibull(x, loc=0, scale=1, shape=1, log = FALSE)
prweibull(q, loc=0, scale=1, shape=1, lower.tail = TRUE)
qrweibull(p, loc=0, scale=1, shape=1, lower.tail = TRUE)
rrweibull(n, loc=0, scale=1, shape=1)
dnweibull(x, loc=0, scale=1, shape=1, log = FALSE)
pnweibull(q, loc=0, scale=1, shape=1, lower.tail = TRUE)
qnweibull(p, loc=0, scale=1, shape=1, lower.tail = TRUE)
rnweibull(n, loc=0, scale=1, shape=1)
x , q |
Vector of quantiles. |
p |
Vector of probabilities. |
n |
Number of observations. |
loc , scale , shape |
Location, scale and shape parameters (can be given as vectors). |
log |
Logical; if |
lower.tail |
Logical; if |
The reverse (or negative) Weibull distribution function with parameters
\code{loc} = a
, \code{scale} = b
and
\code{shape} = s
is
G(z) = \exp\left\{-\left[-\left(\frac{z-a}{b}\right)
\right]^s\right\}
for z < a
and one otherwise, where b > 0
and
s > 0
.
drweibull
and dnweibull
give the density function,
prweibull
and pnweibull
give the distribution function,
qrweibull
and qnweibull
give the quantile function,
rrweibull
and rnweibull
generate random deviates.
Within extreme value theory the reverse Weibull distibution (also known as the negative Weibull distribution) is often referred to as the Weibull distribution. We make a distinction to avoid confusion with the three-parameter distribution used in survival analysis, which is related by a change of sign to the distribution given above.
rfrechet
, rgev
, rgumbel
drweibull(-5:-3, -1, 0.5, 0.8)
prweibull(-5:-3, -1, 0.5, 0.8)
qrweibull(seq(0.9, 0.6, -0.1), 2, 0.5, 0.8)
rrweibull(6, -1, 0.5, 0.8)
p <- (1:9)/10
prweibull(qrweibull(p, -1, 2, 0.8), -1, 2, 0.8)
## [1] 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
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