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Hoeffding's inequality

Hoeffding's inequality, named after Wassily Hoeffding , is a result in probability theory that gives an upper bound on the probability for the sum of random variables to deviate from its expected value.

Suppose

X1, ..., Xn

are independent random variables with finite first and second moments. Furthermore assume that the Xi are bounded, i.e.

\Pr(X_i \in [a_i, b_i]) = 1.

Then for

Sn = X1 + ... + Xn

we have the inequality

\Pr(S_n - \mathbb{E} S_n \geq t) \leq \exp \left( - \frac{2\,t^2}{\sum_{i=1}^n (b_i - a_i)^2} \right).\,

Related inequalities are Markov's inequality and Chernoff's inequality.

Sources

  • Wassily Hoeffding, Probability inequalities for sums of bounded random variables, Journal of the American Statistical Association 58 (301): 13–30, March 1963.
01-04-2007 01:18:14
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