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giniVarCI (version 0.0.1-3)

gparetoII: Gini index for the Pareto (II) distribution with user-defined location, scale and shape parameters

Description

Calculates the Gini index for the Pareto (II) distribution with location parameter \(a\), scale parameter \(b\) and shape parameter \(s\).

Usage

gparetoII(
 location = 0,
 scale = 1,
 shape = 1
)

Value

A numeric value with the Gini index. A NA is returned when a parameter is non-numeric or positive, except the location parameter that can be equal to 0.

Arguments

location

A positive real number specifying the location parameter \(a\) of the Pareto (II) distribution. The default value is location = 0.

scale

A positive real number specifying the scale parameter \(b\) of the Pareto (II) distribution. The default value is scale = 1.

shape

A positive real number specifying the shape parameter \(s\) of the Pareto (II) distribution. The default value is shape = 1.

Author

Juan F Munoz jfmunoz@ugr.es

Jose M Pavia pavia@uv.es

Encarnacion Alvarez encarniav@ugr.es

Details

The Pareto (II) distribution with location parameter \(a\), scale parameter \(b\), shape parameter \(s\) and denoted as \(ParetoII(a,b,s)\), where \(a \geq 0\), \(b>0\) and \(s>0\), has a probability density function given by (Kleiber and Kotz, 2003; Johnson et al., 1995; Yee, 2022) $$f(y)= \displaystyle \frac{s}{b} \left[1 + \left( \frac{y-a}{b}\right)\right]^{-(s+1)},$$ and a cumulative distribution function given by $$F(y)=1-\left(1 + \displaystyle \frac{y-a}{b} \right)^{-s},$$ where \(y>a\).

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 (II) distribution, and \(E[y]\) is the expectation of the distribution. If location is not specified it assumes the default value of 0, and scale and shape assume the default value of 1. The Pareto (II) distribution is related to the Pareto (IV) distribution: \(ParetoII(a,b,s) = ParetoIV(a,b,1,s)\).

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, gparetoI, gparetoIII, gparetoIV, gdagum, gburr, gfisk

Examples

Run this code
# Gini index for the Pareto (II) distribution with parameters 'a = 1', 'b = 1' and 's = 3'.
gparetoII(location = 1, scale = 1, shape = 3)

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