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logarithmic distribution : ウィキペディア英語版
logarithmic distribution

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
:
-\ln(1-p) = p + \frac + \frac + \cdots.

From this we obtain the identity
:\sum_^ \frac \; \frac = 1.
This leads directly to the probability mass function of a Log(''p'')-distributed random variable:
: f(k) = \frac \; \frac
for ''k'' ≥ 1, and where 0 < ''p'' < 1. Because of the identity above, the distribution is properly normalized.
The cumulative distribution function is
: F(k) = 1 + \frac
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 ''X''''i'', ''i'' = 1, 2, 3, ... is an infinite sequence of independent identically distributed random variables each having a Log(''p'') distribution, then
:\sum_^N X_i
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.
The probability mass function ''ƒ'' of this distribution satisfies the recurrence relation
: f(k+1) = \fracf(k); \text f(1) = \frac.
==See also==

* Poisson distribution (also derived from a Maclaurin series)

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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