Logarithmic distribution
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Cumulative distribution function [[File:=![]() | |||
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In probability and statistics, the logarithmic distribution (also known as the logarithmic series distribution or the log-series distribution) is a discrete probability distribution derived from the Maclaurin series expansion
From this we obtain the identity
This leads directly to the probability mass function of a Log(p)-distributed random variable:
for k ≥ 1, and where 0 < p < 1. Because of the identity above, the distribution is properly normalized.
The cumulative distribution function is
where B is the incomplete beta function.
A Poisson mixture of Log(p)-distributed random variables has a negative binomial distribution. In other words, if N is a random variable with a Poisson distribution, and Xi, i = 1, 2, 3, ... is an infinite sequence of independent identically distributed random variables each having a Log(p) distribution, then
has a negative binomial distribution. In this way, the negative binomial distribution is seen to be a compound Poisson distribution.
R.A. Fisher described the logarithmic distribution in a paper that used it to model relative species abundance.[1]
See also
- Poisson distribution (also derived from a Maclaurin series)
References
- ^ Fisher, R.A.; Corbet, A.S.; Williams, C.B. (1943). "The Relation Between the Number of Species and the Number of Individuals in a Random Sample of an Animal Population" (PDF). Journal of Animal Ecology. 12 (1): 42–58. JSTOR 1411.
Further reading
- Johnson, Norman Lloyd (2005). "Chapter 7: Logarithmic and Lagrangian distributions". Univariate discrete distributions (3 ed.). John Wiley & Sons. ISBN 9780471272465.
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suggested) (help) - Weisstein, Eric W. "Log-Series Distribution". MathWorld.