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The Law of the Iterated Logarithm

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Part of the Springer Texts in Statistics book series (STS)

Abstract

The central limit theorem tells us that suitably normalized sums can be approximated by a normal distribution. Although arbitrarily large values may occur, and will occur, one might try to bound the magnitude in some manner. This is what the law of the iterated logarithm (LIL) does, in that it provides a parabolic bound on how large the oscillations of the partial sums may be as a function of the number of summands.

Keywords

Central Limit Theorem Independent Random Variable Iterate Logarithm Normal Random Variable Exponential Bound 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, Inc. 2005

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