Asymptotics and Renewal Approximation in the Online Selection of Increasing Subsequence
classification
🧮 math.PR
math.OC
keywords
subsequenceapproximationincreasinglengthonlineproblemprocessrenewal
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We revisit the problem of maximising the expected length of increasing subsequence that can be selected from a marked Poisson process by an online strategy. Resorting to a natural size variable, the problem is represented in terms of a controlled partially deterministic Markov process with decreasing paths. Refining known estimates we obtain fairly complete asymptotic expansions for the moments, and using a renewal approximation give a novel proof of the central limit theorem for the length of selected subsequence under the optimal strategy.
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