| gengammaUC {VGAM} | R Documentation |
Generalized Gamma Distribution
Description
Density, distribution function, quantile function and random
generation for the generalized gamma distribution with
scale parameter scale,
and parameters d and k.
Usage
dgengamma.stacy(x, scale = 1, d, k, log = FALSE)
pgengamma.stacy(q, scale = 1, d, k,
lower.tail = TRUE, log.p = FALSE)
qgengamma.stacy(p, scale = 1, d, k,
lower.tail = TRUE, log.p = FALSE)
rgengamma.stacy(n, scale = 1, d, k)
Arguments
x, q |
vector of quantiles. |
p |
vector of probabilities. |
n |
number of observations.
Same as in |
scale |
the (positive) scale parameter |
d, k |
the (positive) parameters |
log |
Logical.
If |
lower.tail, log.p |
Details
See gengamma.stacy, the VGAM family function
for estimating the generalized gamma distribution
by maximum likelihood estimation,
for formulae and other details.
Apart from n, all the above arguments may be vectors and
are recyled to the appropriate length if necessary.
Value
dgengamma.stacy gives the density,
pgengamma.stacy gives the distribution function,
qgengamma.stacy gives the quantile function, and
rgengamma.stacy generates random deviates.
Author(s)
T. W. Yee and Kai Huang
References
Stacy, E. W. and Mihram, G. A. (1965). Parameter estimation for a generalized gamma distribution. Technometrics, 7, 349–358.
See Also
Examples
## Not run: x <- seq(0, 14, by = 0.01); d <- 1.5; Scale <- 2; k <- 6
plot(x, dgengamma.stacy(x, Scale, d = d, k = k), type = "l",
col = "blue", ylim = 0:1,
main = "Blue is density, orange is the CDF",
sub = "Purple are 5,10,...,95 percentiles", las = 1, ylab = "")
abline(h = 0, col = "blue", lty = 2)
lines(qgengamma.stacy(seq(0.05, 0.95, by = 0.05), Scale, d = d, k = k),
dgengamma.stacy(qgengamma.stacy(seq(0.05, 0.95, by = 0.05),
Scale, d = d, k = k),
Scale, d = d, k = k), col = "purple", lty = 3, type = "h")
lines(x, pgengamma.stacy(x, Scale, d = d, k = k), col = "orange")
abline(h = 0, lty = 2)
## End(Not run)