These functions provide information about the generalized gamma
distribution with scale parameter equal to m, shape equal
to s, and family parameter equal to f: density,
cumulative distribution, quantiles, log hazard, and random generation.
The generalized gamma distribution has density
$$
f(y) = \frac{\nu y^{\nu-1}}
{(\mu/\sigma)^{\nu\sigma} Gamma(\sigma)} y^{\nu(\sigma-1)}
\exp(-(y \sigma/\mu)^\nu)$$
where \(\mu\) is the scale parameter of the distribution,
\(\sigma\) is the shape, and \(\nu\) is the family
parameter.
\(\nu=1\) yields a gamma distribution, \(\sigma=1\) a
Weibull distribution, and \(\sigma=\infty\) a
log normal distribution.