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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 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 : 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 : ==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)』 ■ウィキペディアで「logarithmic distribution」の詳細全文を読む スポンサード リンク
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