R: The Gompertz distribution

Gompertz {DescTools} | R Documentation

## The Gompertz distribution

### Description

Density, distribution function, quantile function and random generation for the Gompertz distribution with unrestricted shape.

### Usage

    dGompertz(x, shape, rate = 1, log = FALSE)
    pGompertz(q, shape, rate = 1, lower.tail = TRUE, log.p = FALSE)
    qGompertz(p, shape, rate = 1, lower.tail = TRUE, log.p = FALSE)
    rGompertz(n, shape = 1, rate = 1)

### Arguments

`x, q` | vector of quantiles.
`shape, rate` | vector of shape and rate parameters.
`log, log.p` | logical; if TRUE, probabilities p are given as log(p).
`lower.tail` | logical; if TRUE (default), probabilities are P(X <= x), otherwise, P(X > x).
`p` | vector of probabilities.
`n` | number of observations. If `length(n) > 1`, the length is taken to be the number required.

### Details

The Gompertz distribution with `shape` parameter a and `rate` parameter b has probability density function

f(x | a, b) = b exp(ax) exp(-b/a (exp(ax) - 1))

For a=0 the Gompertz is equivalent to the exponential distribution with constant hazard and rate b.

The probability distribution function is

F(x | a, b) = 1 - exp(-b/a (exp(ax) - 1))

Thus if a is negative, letting x tend to infinity shows that there is a non-zero probability 1 - exp(b/a) of living forever. On these occasions `qGompertz` and `rGompertz` will return `Inf`.

### Value

`dGompertz` gives the density, `pGompertz` gives the distribution function, `qGompertz` gives the quantile function, and `rGompertz` generates random deviates.

### Note

Some implementations of the Gompertz restrict a to be strictly positive, which ensures that the probability of survival decreases to zero as x increases to infinity. The more flexible implementation given here is consistent with `streg` in Stata.

The functions `dGompertz` and similar available in the package eha label the parameters the other way round, so that what is called the `shape` there is called the `rate` here, and what is called `1 / scale` there is called the `shape` here. The terminology here is consistent with the exponential `dexp` and Weibull `dweibull` distributions in R.

### Author(s)

Christopher Jackson <chris.jackson@mrc-bsu.cam.ac.uk>

### References

Stata Press (2007) Stata release 10 manual: Survival analysis and epidemiological tables.

### See Also

`dexp`

[Package DescTools version 0.99.38 Index]