ggompertz {giniVarCI} | R Documentation |
Gini index for the Gompertz distribution with user-defined scale and shape parameters
Description
Calculate the Gini index for the Gompertz distribution with scale
parameter \beta
and shape
parameter \alpha
.
Usage
ggompertz(
scale = 1,
shape
)
Arguments
scale |
A positive real number specifying the scale parameter |
shape |
A positive real number specifying the shape parameter |
Details
The Gompertz distribution with scale
parameter \beta
, shape
parameter \alpha
and denoted as Gompertz(\beta, \alpha)
, where \beta>0
and \alpha>0
, has a probability density function given by (Kleiber and Kotz, 2003; Johnson et al., 1995; Rodriguez, 1977; Yee, 2022)
f(y)= \alpha e^{\beta y} \exp\left[ - \displaystyle \frac{\alpha}{\beta}\left(e^{\beta y} - 1 \right) \right],
and a cumulative distribution function given by
F(y)= 1 -\exp\left[ - \displaystyle \frac{\alpha}{\beta}\left(e^{\beta y} - 1 \right) \right],
where y \geq 0
.
The Gini index can be computed as
G = 2\left(0.5 - \displaystyle \frac{1}{E[y]}\int_{0}^{1}\int_{0}^{Q(y)}yf(y)dy\right),
where Q(y)
is the quantile function of the Gompertz distribution, and E[y]
is the expectation of the distribution. If scale
is not specified it assumes the default value of 1.
Value
A numeric value with the Gini index. A NA
is returned when a parameter is non-numeric or non-positive.
Author(s)
Juan F Munoz jfmunoz@ugr.es
Jose M Pavia pavia@uv.es
Encarnacion Alvarez encarniav@ugr.es
References
Kleiber, C. and Kotz, S. (2003). Statistical Size Distributions in Economics and Actuarial Sciences, Hoboken, NJ, USA: Wiley-Interscience.
Johnson, N. L., Kotz, S. and Balakrishnan, N. (1995) Continuous Univariate Distributions, volume 1, chapter 14. Wiley, New York.
Yee, T. W. (2022). VGAM: Vector Generalized Linear and Additive Models. R package version 1.1-7, https://CRAN.R-project.org/package=VGAM.
See Also
ggamma
, gbeta
, gchisq
, gpareto
Examples
# Gini index for the Gompertz distribution with 'scale = 1' and 'shape = 3'.
ggompertz(scale = 1, shape = 3)