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Yule-Simon

Probability mass function Yule-Simon PMF on a log-log scale. (Note that the function is only defined at integer values of k. The connecting lines do not indicate continuity.)
Cumulative distribution function Yule-Simon CMF. (Note that the function is only defined at integer values of k. The connecting lines do not indicate continuity.)
Parameters	shape (real)
Support
Probability mass function (pmf)
Cumulative distribution function (cdf)
Mean	for
Median
Mode
Variance	for
Skewness	for
Excess kurtosis	for
Entropy
Moment-generating function (mgf)
Characteristic function

In probability and statistics, the Yule-Simon distribution is a discrete probability distribution named after Udny Yule and Herbert Simon. Simon originally called it the Yule distribution.

The probability mass function of the Yule-Simon(ρ) distribution is

for integer and real ρ > 0, where B is the beta function. Equivalently the pmf can be written in terms of the falling factorial as

where Γ is the gamma function. Thus, if ρ is an integer,

The probability mass function f has the property that for sufficiently large k we have

This means that the tail of the Yule-Simon distribution is a realization of Zipf's law: f(k;ρ) can be used to model, for example, the relative frequency of the kth most frequent word in a large collection of text, which according to Zipf's law is inversely proportional to a (typically small) power of k.

The Yule-Simon distribution arises as a continuous mixture of geometric distributions. Specifically, assume that W follows an exponential distribution with scale 1 / ρ or rate ρ:

Then a Yule-Simon distributed variable K has the following geometric distribution:

The pmf of a geometric distribution is

for . The Yule-Simon pmf is then the following exponential-geometric mixture distribution:

The two-parameter generalization of the original Yule distribution replaces the beta function with an incomplete beta function. The probability mass function of the generalized Yule-Simon(ρ, α) distribution is defined as

with . For α = 0 the ordinary Yule-Simon(ρ) distribution is obtained as a special case. The use of the incomplete beta function has the effect of introducing an exponential cutoff in the upper tail.

• Herbert A. Simon, On a Class of Skew Distribution Functions, Biometrika 42(3/4): 425–440, December 1955.
• Colin Rose and Murray D. Smith, Mathematical Statistics with Mathematica. New York: Springer, 2002, ISBN 0-387-95234-9. (See page 107, where it is called the "Yule distribution".)

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