Optimal Stopping of a Random Sequence with Unknown Distribution

Alexander Goldenshluger, Assaf Zeevi

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The subject of this paper is the problem of optimal stopping of a sequence of independent and identically distributed random variables with unknown distribution. We propose a stopping rule that is based on relative ranks and study its performance as measured by the maximal relative regret over suitable nonparametric classes of distributions. It is shown that the proposed rule is first-order asymptotically optimal and nearly rate optimal in terms of the rate at which the relative regret converges to zero. We also develop a general method for numerical solution of sequential stopping problems with no distributional information and use it in order to implement the proposed stopping rule. Some numerical experiments illustrating performance of the rule are presented as well.

Original languageEnglish
Pages (from-to)29-49
Number of pages21
JournalMathematics of Operations Research
Volume47
Issue number1
DOIs
StatePublished - Feb 2022
Externally publishedYes

Funding

FundersFunder number
National Science FoundationCNS-0964170

    Keywords

    • Extreme-value distributions
    • Minimax regret
    • No information
    • Optimal stopping
    • Relative ranks
    • Secretary problems

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