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In [[probability theory]], '''Le Cam's theorem''', named after [[Lucien le Cam]] (1924 – 2000), is as follows.
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Suppose:
 
* ''X''<sub>1</sub>, ..., ''X''<sub>''n''</sub> are [[statistical independence|independent]] [[random variable]]s, each with a [[Bernoulli distribution]] (i.e., equal to either 0 or 1), not necessarily identically distributed.
 
* Pr(''X''<sub>''i''</sub> = 1) = ''p''<sub>''i''</sub> for ''i'' = 1, 2, 3, ...
 
* <math>\lambda_n = p_1 + \cdots + p_n.\,</math>
 
* <math>S_n = X_1 + \cdots + X_n.\,</math>  (i.e. <math>S_n</math> follows a [[Poisson binomial distribution]])
 
Then
 
:<math>\sum_{k=0}^\infty \left| \Pr(S_n=k) - {\lambda_n^k e^{-\lambda_n} \over k!} \right| < 2 \sum_{i=1}^n p_i^2. </math>
 
In other words, the sum has approximately a [[Poisson distribution]].
 
By setting ''p''<sub>''i''</sub> = λ<sub>''n''</sub>/''n'', we see that this generalizes the usual [[Poisson limit theorem]].
 
==References==
* {{cite journal
|last=Le Cam |first=L. |authorlink=Lucien le Cam
|title=An Approximation Theorem for the Poisson Binomial Distribution
|journal=Pacific Journal of Mathematics
|volume=10 |issue=4 |pages=1181&ndash;1197 |year=1960
|url=http://projecteuclid.org/euclid.pjm/1103038058 |accessdate=2009-05-13
|mr=0142174 | zbl = 0118.33601
}}
* {{cite conference
|last=Le Cam |first=L. |authorlink=Lucien le Cam
|title=On the Distribution of Sums of Independent Random Variables
|booktitle=Bernoulli, Bayes, Laplace: Proceedings of an International Research Seminar
|editor1=[[Jerzy Neyman]] |editor2=Lucien le Cam
|publisher=Springer-Verlag |location=New York
|pages=179&ndash;202 |year=1963
|mr=0199871
}}
* {{cite jstor|2325124}}
 
==External links==
* {{MathWorld|urlname=LeCamsInequality|title=Le Cam's Inequality}}
 
[[Category:Probability theorems]]
[[Category:Probabilistic inequalities]]
[[Category:Statistical inequalities]]
[[Category:Statistical theorems]]

Latest revision as of 00:26, 27 December 2014

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