Eaton's inequality: Difference between revisions
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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> |
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==Statement of the inequality== |
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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 |
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<math> \sum_{ i = 1 }^n a_i^2 = 1 </math> |
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The inequality concerns the bounds of the sum |
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<math> \sum_{ i = 1 }^n a_i X_i </math> |
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Eaton showed that |
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<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> |
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where ''φ''( x ) is the normal probability density. |
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==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 ≤ i ≤ n. 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
- ^ Eaton ML (1974) A probability inequality for linear combinations of bounded random variables. Ann Statist 2(3) 609-614