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factorial moment generating function : ウィキペディア英語版
factorial moment generating function

In probability theory and statistics, the factorial moment generating function of the probability distribution of a real-valued random variable ''X'' is defined as
:M_X(t)=\operatorname\bigl()
for all complex numbers ''t'' for which this expected value exists. This is the case at least for all ''t'' on the unit circle |t|=1, see characteristic function. If ''X'' is a discrete random variable taking values only in the set of non-negative integers, then M_X is also called probability-generating function of ''X'' and M_X(t) is well-defined at least for all ''t'' on the closed unit disk |t|\le1.
The factorial moment generating function generates the factorial moments of the probability distribution.
Provided M_X exists in a neighbourhood of ''t'' = 1, the ''n''th factorial moment is given by 〔http://homepages.nyu.edu/~bpn207/Teaching/2005/Stat/Generating_Functions.pdf〕
:\operatorname()=M_X^(1)=\left.\frac\right|_ M_X(t),
where the Pochhammer symbol (''x'')''n'' is the falling factorial
:(x)_n = x(x-1)(x-2)\cdots(x-n+1).\,
(Many mathematicians, especially in the field of special functions, use the same notation to represent the rising factorial.)
==Example==
Suppose ''X'' has a Poisson distribution with expected value λ, then its factorial moment generating function is
:M_X(t)
=\sum_^\infty t^k\underbrace_
=e^\sum_^\infty \frac = e^,\qquad t\in\mathbb,

(use the definition of the exponential function) and thus we have
:\operatorname()=\lambda^n.

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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