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Logarithmic distribution

From Wikipedia, the free encyclopedia

Logarithmic
Probability mass function
The function is only defined at integer values. The connecting lines are merely guides for the eye.
Cumulative distribution function
Parameters
Support
pmf
CDF
Mean
Mode
Variance
MGF
CF
PGF

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 compounded with 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]

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Transcription

See also

References

  1. ^ 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. doi:10.2307/1411. JSTOR 1411. Archived from the original (PDF) on 2011-07-26.

Further reading

This page was last edited on 22 September 2019, at 05:26
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