dGGD {RelDists} | R Documentation |
The Generalized Gompertz distribution
Description
Density, distribution function, quantile function,
random generation and hazard function for the generalized Gompertz distribution with
parameters mu
sigma
and nu
.
Usage
dGGD(x, mu, sigma, nu, log = FALSE)
pGGD(q, mu, sigma, nu, lower.tail = TRUE, log.p = FALSE)
qGGD(p, mu, sigma, nu, lower.tail = TRUE, log.p = FALSE)
rGGD(n, mu, sigma, nu)
hGGD(x, mu, sigma, nu)
Arguments
x , q |
vector of quantiles. |
mu , nu |
scale parameter. |
sigma |
shape 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. |
Details
The Generalized Gompertz Distribution with parameters mu
,
sigma
and nu
has density given by
f(x)= \nu \mu \exp(-\frac{\mu}{\sigma}(\exp(\sigma x - 1))) (1 - \exp(-\frac{\mu}{\sigma}(\exp(\sigma x - 1))))^{(\nu - 1)} ,
for x \geq 0
, \mu > 0
, \sigma \geq 0
and \nu > 0
.
Value
dGGD
gives the density, pGGD
gives the distribution
function, qGGD
gives the quantile function, rGGD
generates random deviates and hGGD
gives the hazard function.
Author(s)
Johan David Marin Benjumea, johand.marin@udea.edu.co
References
El-Gohary A, Alshamrani A, Al-Otaibi AN (2013). “The generalized Gompertz distribution.” Applied Mathematical Modelling, 37(1-2), 13–24.
Examples
old_par <- par(mfrow = c(1, 1)) # save previous graphical parameters
## The probability density function
par(mfrow = c(1, 1))
curve(dGGD(x, mu=1, sigma=0.3, nu=1.5), from = 0, to = 4,
col = "red", las = 1, ylab = "f(x)")
## The cumulative distribution and the Reliability function
par(mfrow = c(1, 2))
curve(pGGD(x, mu=1, sigma=0.3, nu=1.5), from = 0, to = 4,
ylim = c(0, 1), col = "red", las = 1, ylab = "F(x)")
curve(pGGD(x, mu=1, sigma=0.3, nu=1.5, lower.tail = FALSE),
from = 0, to = 4, ylim = c(0, 1), col = "red", las = 1, ylab = "R(x)")
## The quantile function
p <- seq(from = 0, to = 0.99999, length.out = 100)
plot(x = qGGD(p=p, mu=1, sigma=0.3, nu=1.5), y = p,
xlab = "Quantile", las = 1, ylab = "Probability")
curve(pGGD(x, mu=1, sigma=0.3, nu=1.5), from = 0, add = TRUE,
col = "red")
## The random function
hist(rGGD(1000, mu=1, sigma=0.3, nu=1.5), freq = FALSE, xlab = "x",
las = 1, ylim = c(0, 0.7), main = "")
curve(dGGD(x,mu=1, sigma=0.3, nu=1.5), from = 0, to =8, add = TRUE,
col = "red")
## The Hazard function
par(mfrow=c(1,1))
curve(hGGD(x, mu=1, sigma=0.3, nu=1.5), from = 0, to = 3, col = "red",
ylab = "The hazard function", las = 1)
par(old_par) # restore previous graphical parameters