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This inequality was described in 1974 by Eaton.<ref name=Eaton1974>Eaton ML (1974) A probability inequality for linear combinations of bounded random variables. Ann Statist 2(3) 609-614 </ref>
This inequality was described in 1974 by Eaton.<ref name=Eaton1974>Eaton ML (1974) A probability inequality for linear combinations of bounded random variables. Ann Statist 2(3) 609-614 </ref>

==Statement of the inequality==

Let ''X''<sub>i</sub> be a set of real independent random variables each with a [[mean]] of [[zero]] and bounded by 1 ( |''X''<sub>i</sub>| ≤ 1). Let 1 ≤ ''i'' ≤ ''n''. The variates do not have to be identically or symmetrically distributed. Let ''a''<sub>i</sub> be a set of ''n'' fixed real numbers with

<math> \sum_{ i = 1 }^n a_i^2 = 1 </math>

The inequality concerns the bounds of the sum

<math> \sum_{ i = 1 }^n a_i X_i </math>

Eaton showed that

<math> P( | \sum_{ i = 1 }^n a_i X_i | \ge k ) \le 2 \inf_{ 0 \le c \le k } \int_c^\infty ( \frac{ z - c }{ k - c } )^3 \phi( z ) dz = 2 B_E( k )</math>

where ''φ''( x ) is the normal probability density.


==References==
==References==

Revision as of 09:13, 24 February 2013

Eaton's inequality is a bound on the maximal values of a linear combination of bounded random variables.

History

This inequality was described in 1974 by Eaton.[1]

Statement of the inequality

Let Xi be a set of real independent random variables each with a mean of zero and bounded by 1 ( |Xi| ≤ 1). Let 1 ≤ in. The variates do not have to be identically or symmetrically distributed. Let ai be a set of n fixed real numbers with

The inequality concerns the bounds of the sum

Eaton showed that

where φ( x ) is the normal probability density.

References

  1. ^ Eaton ML (1974) A probability inequality for linear combinations of bounded random variables. Ann Statist 2(3) 609-614