Density, cumulative distribution function, quantile function and random generation for the Perks distribution.
dperks(x, scale = 1, shape, log = FALSE)
pperks(q, scale = 1, shape, lower.tail = TRUE, log.p = FALSE)
qperks(p, scale = 1, shape, lower.tail = TRUE, log.p = FALSE)
rperks(n, scale = 1, shape)
vector of quantiles.
vector of probabilities.
number of observations.
Same as in runif
.
Logical.
If log = TRUE
then the logarithm of the density is returned.
positive shape and scale parameters.
dperks
gives the density,
pperks
gives the cumulative distribution function,
qperks
gives the quantile function, and
rperks
generates random deviates.
See perks
for details.
# NOT RUN {
probs <- seq(0.01, 0.99, by = 0.01)
Shape <- exp(-1.0); Scale <- exp(1);
max(abs(pperks(qperks(p = probs, Shape, Scale),
Shape, Scale) - probs)) # Should be 0
# }
# NOT RUN {
x <- seq(-0.1, 07, by = 0.01);
plot(x, dperks(x, 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, pperks(x, Shape, Scale), col = "orange")
probs <- seq(0.1, 0.9, by = 0.1)
Q <- qperks(probs, Shape, Scale)
lines(Q, dperks(Q, Shape, Scale), col = "purple", lty = 3, type = "h")
pperks(Q, Shape, Scale) - probs # Should be all zero
abline(h = probs, col = "purple", lty = 3)
# }
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