Champernowne distribution
In statistics, the Champernowne distribution is a symmetric, continuous probability distribution, describing random variables that take both positive and negative values. It is a generalization of the logistic distribution that was introduced by D. G. Champernowne.[1][2][3] Champernowne developed the distribution to describe the logarithm of income.[2]
Definition
The Champernowne distribution has a probability density function given by
where 
 are positive parameters, and n is the normalizing constant, which depends on the parameters. The density may be rewritten as
using the fact that 
Properties
The density f(y) defines a symmetric distribution with median y0, which has tails somewhat heavier than a normal distribution.
Special cases
In the special case 
 it is the Burr Type XII density.
When 
, 
which is the density of the standard logistic distribution.
Distribution of income
If the distribution of Y, the logarithm of income, has a Champernowne distribution, then the density function of the income X = exp(Y) is[1]
where x0 = exp(y0) is the median income. If λ = 1, this distribution is often called the Fisk distribution,[4] which has density
See also
References
- 1 2 C. Kleiber and S. Kotz (2003). Statistical Size Distributions in Economics and Actuarial Sciences. New York: Wiley. Section 7.3 "Champernowne Distribution."
 - 1 2 Champernowne, D. G. (1952). "The graduation of income distributions". Econometrica 20: 591–614. doi:10.2307/1907644. JSTOR 1907644.
 - ↑ Champernowne, D. G. (1953). "A Model of Income Distribution". The Economic Journal 63 (250): 318–351. doi:10.2307/2227127. JSTOR 2227127.
 - ↑ Fisk, P. R. (1961). "The graduation of income distributions". Econometrica 29: 171–185. doi:10.2307/1909287.
 
![f(y;\alpha, \lambda, y_0 ) = \frac{n}{\cosh[\alpha(y - y_0)] + \lambda}, \qquad -\infty < y < \infty,](../I/m/65679587dc4a28ae4e95fc85a2235da7.png)


![f(x) = \frac{n}{x [1/2(x/x_0)^{-\alpha} + \lambda + a/2(x/x_0)^\alpha ]}, \qquad x > 0,](../I/m/02ee47d96cc6f5dba473bcecccf500a9.png)
![f(x) = \frac{\alpha x^{\alpha - 1}}{x_0^\alpha [1 + (x/x_0)^\alpha]^2}, \qquad x > 0.](../I/m/46082781f95fbab53f844a1a9af576aa.png)