rweibull {evd} | R Documentation |
Density function, distribution function, quantile function and random generation for the reversed 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)
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 TRUE , the log density is returned. |
lower.tail |
Logical; if TRUE (default), probabilities
are P[X <= x], otherwise, P[X > x] |
The reversed Weibull distribution function with parameters
loc
= a, scale
= b and
shape
= s is
G(x) = exp{-[-(z-a)/b]^s}
for z < a and one otherwise, where b > 0 and s > 0.
drweibull
gives the density function, prweibull
gives the distribution function, qrweibull
gives the
quantile function, and rrweibull
generates random deviates.
Within extreme value theory the reversed Weibull distibution is usually referred to as the Weibull distribution. I 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.
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