gparetoI {giniVarCI} | R Documentation |
Gini index for the Pareto (I) distribution with user-defined scale and shape parameters
Description
Calculate the Gini index for the Pareto (I) distribution with scale
parameter b
and shape
parameter s
.
Usage
gparetoI(
scale = 1,
shape = 1
)
Arguments
scale |
A positive real number specifying the scale parameter |
shape |
A positive real number specifying the shape parameter |
Details
The Pareto (I) distribution with scale
parameter b
, shape
parameter s
and denoted as ParetoI(b,s)
, where b>0
and s>0
, has a probability density function given by (Kleiber and Kotz, 2003; Johnson et al., 1995; Yee, 2022)
f(y)= \displaystyle \frac{s}{b} \left(\frac{y}{b}\right)^{-(s+1)},
and a cumulative distribution function given by
F(y)=1 - \displaystyle \left(\frac{y}{b}\right)^{-s},
where y>b
.
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 Pareto (I) distribution, and E[y]
is the expectation of the distribution. If scale
or shape
are not specified they assume the default value of 1. The Pareto (I) distribution is related to the Pareto (IV) distribution: ParetoI(b,s) = ParetoIV(b,b,1,s)
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
gpareto
, gparetoII
, gparetoIII
, gparetoIV
, gdagum
, gburr
, gfisk
Examples
# Gini index for the Pareto (I) distribution with scale 'b = 1' and shape 's = 3'.
gparetoI(scale = 1, shape = 3)