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An inequality giving an estimate of the deviation of the distribution function of a sum of independent random variables from the normal distribution function. Let <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b015/b015760/b0157601.png" /> be independent random variables with the same distribution such that
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An inequality giving an estimate of the deviation of the distribution function of a sum of independent random variables from the normal distribution function. Let $X_1,\ldots,X_n$ be independent random variables with the same distribution such that
  
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b015/b015760/b0157602.png" /></td> </tr></table>
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$$\mathbf{E}X_j=0$,\quad \mathbf{E}X_j^2=\sigma^2>0,\quad\mathbf{E}\lvert X_j\rvert^3<\infty.$$
  
 
Let
 
Let
  
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b015/b015760/b0157603.png" /></td> </tr></table>
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$$\rho=\frac{\mathbf{E}\lvert X_j\rvert^3}{\sigma^3}$$
  
 
and
 
and
  
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b015/b015760/b0157604.png" /></td> </tr></table>
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$$\Phi(x)=\frac{1}{\sqrt{2\pi}}\int_{-\infty}^x e^{-t^2/2}\,\mathrm{d}t;$$
  
then, for any <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b015/b015760/b0157605.png" />,
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then, for any $n$,
  
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b015/b015760/b0157606.png" /></td> </tr></table>
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$$\sup_x\left\lvert\mathbf{P}\left\{\frac{1}{\sigma\sqrt{n}}\sum_{j=1}^nX_j\leq x\right\}-\Phi(x)\right\rvert\leq A\frac{\rho}{\sqrt{n}},$$
  
where <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b015/b015760/b0157607.png" /> is an absolute positive constant. This result was obtained by A.C. Berry [[#References|[1]]] and, independently, by C.G. Esseen [[#References|[2]]].
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where $A$ is an absolute positive constant. This result was obtained by A.C. Berry {{Cite|Be}} and, independently, by C.G. Esseen {{Cite|Es}}. The constant $A$ can be taken to be $33/4$ , see {{Cite|Fe|p. 515}}.
  
 
====References====
 
====References====
<table><TR><TD valign="top">[1]</TD> <TD valign="top"> A.C. Berry,  "The accuracy of the Gaussian approximation to the sum of independent variables"  ''Trans. Amer. Math. Soc.'' , '''49'''  (1941)  pp. 122–136</TD></TR><TR><TD valign="top">[2]</TD> <TD valign="top"> C.G. Esseen,  "On the Liapunoff limit of error in the theory of probability"  ''Ark. Mat. Astr. Fysik'' , '''28A''' :  2  (1942)  pp. 1–19</TD></TR><TR><TD valign="top">[3]</TD> <TD valign="top">  V.V. Petrov,  "Sums of independent random variables" , Springer  (1975)  (Translated from Russian)</TD></TR></table>
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{|
 
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|-
 
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|valign="top"|{{Ref|Be}}||valign="top"| A.C. Berry,  "The accuracy of the Gaussian approximation to the sum of independent variables"  ''Trans. Amer. Math. Soc.'' , '''49'''  (1941)  pp. 122–136
 
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====Comments====
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|valign="top"|{{Ref|Es}}||valign="top"| C.G. Esseen,  "On the Liapunoff limit of error in the theory of probability"  ''Ark. Mat. Astr. Fysik'' , '''28A''' :  2  (1942)  pp. 1–19
The constant <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b015/b015760/b0157608.png" /> can be taken to be <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b015/b015760/b0157609.png" />, cf. [[#References|[a1]]], p. 515 ff.
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|-
 
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|valign="top"|{{Ref|Fe}}||valign="top"| W. Feller,   "An introduction to probability theory and its applications" , '''2''' , Wiley  (1966)  pp. 210
====References====
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<table><TR><TD valign="top">[a1]</TD> <TD valign="top"> W. Feller,   "An introduction to probability theory and its applications" , '''2''' , Wiley  (1966)  pp. 210</TD></TR></table>
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|valign="top"|{{Ref|Pe}}||valign="top"| V.V. Petrov,  "Sums of independent random variables" , Springer  (1975)  (Translated from Russian)
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|-
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Revision as of 10:57, 22 April 2012

An inequality giving an estimate of the deviation of the distribution function of a sum of independent random variables from the normal distribution function. Let $X_1,\ldots,X_n$ be independent random variables with the same distribution such that

$$\mathbf{E}X_j=0$,\quad \mathbf{E}X_j^2=\sigma^2>0,\quad\mathbf{E}\lvert X_j\rvert^3<\infty.$$

Let

$$\rho=\frac{\mathbf{E}\lvert X_j\rvert^3}{\sigma^3}$$

and

$$\Phi(x)=\frac{1}{\sqrt{2\pi}}\int_{-\infty}^x e^{-t^2/2}\,\mathrm{d}t;$$

then, for any $n$,

$$\sup_x\left\lvert\mathbf{P}\left\{\frac{1}{\sigma\sqrt{n}}\sum_{j=1}^nX_j\leq x\right\}-\Phi(x)\right\rvert\leq A\frac{\rho}{\sqrt{n}},$$

where $A$ is an absolute positive constant. This result was obtained by A.C. Berry [Be] and, independently, by C.G. Esseen [Es]. The constant $A$ can be taken to be $33/4$ , see [Fe, p. 515].

References

[Be] A.C. Berry, "The accuracy of the Gaussian approximation to the sum of independent variables" Trans. Amer. Math. Soc. , 49 (1941) pp. 122–136
[Es] C.G. Esseen, "On the Liapunoff limit of error in the theory of probability" Ark. Mat. Astr. Fysik , 28A : 2 (1942) pp. 1–19
[Fe] W. Feller, "An introduction to probability theory and its applications" , 2 , Wiley (1966) pp. 210
[Pe] V.V. Petrov, "Sums of independent random variables" , Springer (1975) (Translated from Russian)
How to Cite This Entry:
Berry-Esseen inequality. Encyclopedia of Mathematics. URL: http://encyclopediaofmath.org/index.php?title=Berry-Esseen_inequality&oldid=25038
This article was adapted from an original article by V.V. Petrov (originator), which appeared in Encyclopedia of Mathematics - ISBN 1402006098. See original article