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Champernowne distribution

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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. Champernowne developed the distribution to describe the logarithm of income.

Definition

The Champernowne distribution has a probability density function given by

f ( y ; α , λ , y 0 ) = n cosh [ α ( y y 0 ) ] + λ , < y < , {\displaystyle f(y;\alpha ,\lambda ,y_{0})={\frac {n}{\cosh+\lambda }},\qquad -\infty <y<\infty ,}

where α , λ , y 0 {\displaystyle \alpha ,\lambda ,y_{0}} are positive parameters, and n is the normalizing constant, which depends on the parameters. The density may be rewritten as

f ( y ) = n 1 2 e α ( y y 0 ) + λ + 1 2 e α ( y y 0 ) , {\displaystyle f(y)={\frac {n}{{\tfrac {1}{2}}e^{\alpha (y-y_{0})}+\lambda +{\tfrac {1}{2}}e^{-\alpha (y-y_{0})}}},}

using the fact that cosh x = 1 2 ( e x + e x ) . {\displaystyle \cosh x={\tfrac {1}{2}}(e^{x}+e^{-x}).}

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 λ = 0 {\displaystyle \lambda =0} ( α = π 2 , y 0 = 0 {\displaystyle \alpha ={\tfrac {\pi }{2}},y_{0}=0} ) it is the hyperbolic secant distribution.

In the special case λ = 1 {\displaystyle \lambda =1} it is the Burr Type XII density.

When y 0 = 0 , α = 1 , λ = 1 {\displaystyle y_{0}=0,\alpha =1,\lambda =1} ,

f ( y ) = 1 e y + 2 + e y = e y ( 1 + e y ) 2 , {\displaystyle f(y)={\frac {1}{e^{y}+2+e^{-y}}}={\frac {e^{y}}{(1+e^{y})^{2}}},}

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

f ( x ) = n x [ 1 / 2 ( x / x 0 ) α + λ + a / 2 ( x / x 0 ) α ] , x > 0 , {\displaystyle f(x)={\frac {n}{x}},\qquad x>0,}

where x0 = exp(y0) is the median income. If λ = 1, this distribution is often called the Fisk distribution, which has density

f ( x ) = α x α 1 x 0 α [ 1 + ( x / x 0 ) α ] 2 , x > 0. {\displaystyle f(x)={\frac {\alpha x^{\alpha -1}}{x_{0}^{\alpha }^{2}}},\qquad x>0.}

See also

References

  1. ^ C. Kleiber and S. Kotz (2003). Statistical Size Distributions in Economics and Actuarial Sciences. New York: Wiley. Section 7.3 "Champernowne Distribution."
  2. ^ Champernowne, D. G. (1952). "The graduation of income distributions". Econometrica. 20 (4): 591–614. doi:10.2307/1907644. JSTOR 1907644.
  3. Champernowne, D. G. (1953). "A Model of Income Distribution". The Economic Journal. 63 (250): 318–351. doi:10.2307/2227127. JSTOR 2227127.
  4. Fisk, P. R. (1961). "The graduation of income distributions". Econometrica. 29 (2): 171–185. doi:10.2307/1909287. JSTOR 1909287.
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