# GGamma: Generalized Gamma Distribution In rmutil: Utilities for Nonlinear Regression and Repeated Measurements Models

## Description

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) = fy^(f-1)/((m/s)^(fs) Gamma(s)) y^(f(s-1)) exp(-(y s/m)^f)

where m is the scale parameter of the distribution, s is the shape, and f is the family parameter.

f=1 yields a gamma distribution, s=1 a Weibull distribution, and s=infinity a log normal distribution.

## Usage

 ```1 2 3 4``` ```dggamma(y, s, m, f, log=FALSE) pggamma(q, s, m, f) qggamma(p, s, m, f) rggamma(n, s, m, f) ```

## Arguments

 `y` vector of responses. `q` vector of quantiles. `p` vector of probabilities `n` number of values to generate `m` vector of location parameters. `s` vector of dispersion parameters. `f` vector of family parameters. `log` if TRUE, log probabilities are supplied.

## Author(s)

J.K. Lindsey

`dgamma` for the gamma distribution, `dweibull` for the Weibull distribution, `dlnorm` for the log normal distribution.
 ```1 2 3 4``` ```dggamma(2, 5, 4, 2) pggamma(2, 5, 4, 2) qggamma(0.75, 5, 4, 2) rggamma(10, 5, 4, 2) ```