
Density, cumulative distribution function, quantile function and random generation for the Gompertz distribution.
dgompertz(x, scale = 1, shape, log = FALSE)
pgompertz(q, scale = 1, shape, lower.tail = TRUE, log.p = FALSE)
qgompertz(p, scale = 1, shape, lower.tail = TRUE, log.p = FALSE)
rgompertz(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 scale and shape parameters.
dgompertz
gives the density,
pgompertz
gives the cumulative distribution function,
qgompertz
gives the quantile function, and
rgompertz
generates random deviates.
See gompertz
for details.
# NOT RUN {
probs <- seq(0.01, 0.99, by = 0.01)
Shape <- exp(1); Scale <- exp(1)
max(abs(pgompertz(qgompertz(p = probs, Scale, shape = Shape),
Scale, shape = Shape) - probs)) # Should be 0
# }
# NOT RUN {
x <- seq(-0.1, 1.0, by = 0.001)
plot(x, dgompertz(x, Scale,shape = Shape), 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 = "")
abline(h = 0, col = "blue", lty = 2)
lines(x, pgompertz(x, Scale, shape = Shape), col = "orange")
probs <- seq(0.1, 0.9, by = 0.1)
Q <- qgompertz(probs, Scale, shape = Shape)
lines(Q, dgompertz(Q, Scale, shape = Shape), col = "purple",
lty = 3, type = "h")
pgompertz(Q, Scale, shape = Shape) - probs # Should be all zero
abline(h = probs, col = "purple", lty = 3)
# }
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