Gompertz {flexsurv}

The Gompertz distribution

Description

Density, distribution function, hazards, 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)

hgompertz(x, shape, rate = 1, log = FALSE)

Hgompertz(x, shape, rate = 1, log = FALSE)

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 \le 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) = be^{ax}\exp(-b/a (e^{ax} - 1))

and hazard

h(x | a, b) = b e^{ax}

The hazard is increasing for shape a>0 and decreasing for a<0. 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 (e^{ax} - 1))

Thus if a is negative, letting x tend to infinity shows that there is a non-zero probability \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, hgompertz gives the hazard function, Hgompertz gives the cumulative hazard 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 eha::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 <[e-mail]>

References

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

See Also

dexp