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

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