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.
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© 2005 Springer Science+Business Media, Inc.
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(2005). The Law of the Iterated Logarithm. In: Probability: A Graduate Course. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/0-387-27332-8_8
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DOI: https://doi.org/10.1007/0-387-27332-8_8
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-22833-4
Online ISBN: 978-0-387-27332-7
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