Density, cumulative distribution function, quantile function and random generation for the Makeham distribution.
dmakeham(x, scale = 1, shape, epsilon = 0, log = FALSE)
pmakeham(q, scale = 1, shape, epsilon = 0, lower.tail = TRUE, log.p = FALSE)
qmakeham(p, scale = 1, shape, epsilon = 0, lower.tail = TRUE, log.p = FALSE)
rmakeham(n, scale = 1, shape, epsilon = 0)
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.
another parameter. Must be non-negative. See below.
dmakeham
gives the density,
pmakeham
gives the cumulative distribution function,
qmakeham
gives the quantile function, and
rmakeham
generates random deviates.
See makeham
for details.
The default value of epsilon = 0
corresponds
to the Gompertz distribution.
The function pmakeham
uses lambertW
.
Jodra, P. (2009). A closed-form expression for the quantile function of the Gompertz-Makeham distribution. Mathematics and Computers in Simulation, 79, 3069--3075.
# NOT RUN {
probs <- seq(0.01, 0.99, by = 0.01)
Shape <- exp(-1); Scale <- exp(1); eps = Epsilon <- exp(-1)
max(abs(pmakeham(qmakeham(p = probs, sca = Scale, Shape, eps = Epsilon),
sca = Scale, Shape, eps = Epsilon) - probs)) # Should be 0
# }
# NOT RUN {
x <- seq(-0.1, 2.0, by = 0.01);
plot(x, dmakeham(x, sca = Scale, Shape, eps = Epsilon), type = "l",
main = "Blue is density, orange is cumulative distribution function",
sub = "Purple lines are the 10,20,...,90 percentiles",
col = "blue", las = 1, ylab = "")
abline(h = 0, col = "blue", lty = 2)
lines(x, pmakeham(x, sca = Scale, Shape, eps = Epsilon), col = "orange")
probs <- seq(0.1, 0.9, by = 0.1)
Q <- qmakeham(probs, sca = Scale, Shape, eps = Epsilon)
lines(Q, dmakeham(Q, sca = Scale, Shape, eps = Epsilon),
col = "purple", lty = 3, type = "h")
pmakeham(Q, sca = Scale, Shape, eps = Epsilon) - probs # Should be all zero
abline(h = probs, col = "purple", lty = 3)
# }
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