Optimal Sequential Selection of a Monotone Sequence From a Random Sample
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Statistics Papers
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monotone subsequence
optimal stopping
subadditive process
Physical Sciences and Mathematics
optimal stopping
subadditive process
Physical Sciences and Mathematics
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Samuels, Stephen
Steele, J Michael
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Abstract
The length of the longest monotone increasing subsequence of a random sample of size n is known to have expected value asymptotic to 2n1/2. We prove that it is possible to make sequential choices which give an increasing subsequence of expected length asymptotic to (2n)1/2. Moreover, this rate of increase is proved to be asymptotically best possible.
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1981-04-01
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The Annals of Probability
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At the time of publication, author J. Michael Steele was affiliated with Stanford University. Currently, he is a faculty member at the Statistics Department at the University of Pennsylvania.