| Gumbel-II {VGAM} | R Documentation |
Density, cumulative distribution function, quantile function and random generation for the Gumbel-II distribution.
dgumbelII(x, scale = 1, shape, log = FALSE) pgumbelII(q, scale = 1, shape, lower.tail = TRUE, log.p = FALSE) qgumbelII(p, scale = 1, shape, lower.tail = TRUE, log.p = FALSE) rgumbelII(n, scale = 1, shape)
x, q |
vector of quantiles. |
p |
vector of probabilities. |
n |
number of observations.
Same as in |
log |
Logical.
If |
lower.tail, log.p |
|
shape, scale |
positive shape and scale parameters. |
See gumbelII for details.
dgumbelII gives the density,
pgumbelII gives the cumulative distribution function,
qgumbelII gives the quantile function, and
rgumbelII generates random deviates.
T. W. Yee and Kai Huang
probs <- seq(0.01, 0.99, by = 0.01)
Scale <- exp(1); Shape <- exp( 0.5);
max(abs(pgumbelII(qgumbelII(p = probs, shape = Shape, Scale),
shape = Shape, Scale) - probs)) # Should be 0
## Not run: x <- seq(-0.1, 10, by = 0.01);
plot(x, dgumbelII(x, shape = Shape, Scale), type = "l", col = "blue", las = 1,
main = "Blue is density, orange is cumulative distribution function",
sub = "Purple lines are the 10,20,...,90 percentiles",
ylab = "", ylim = 0:1)
abline(h = 0, col = "blue", lty = 2)
lines(x, pgumbelII(x, shape = Shape, Scale), col = "orange")
probs <- seq(0.1, 0.9, by = 0.1)
Q <- qgumbelII(probs, shape = Shape, Scale)
lines(Q, dgumbelII(Q, Scale, Shape), col = "purple", lty = 3, type = "h")
pgumbelII(Q, shape = Shape, Scale) - probs # Should be all zero
abline(h = probs, col = "purple", lty = 3)
## End(Not run)