Eaton's inequality: Difference between revisions
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<math> \sum_{ i = 1 }^n a_i^2 = 1 </math> |
<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 |
Eaton showed that |
Revision as of 09:14, 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
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