Optimal Online Selection of an Alternating Subsequence: A Central Limit Theorem

We analyze the optimal policy for the sequential selection of an alternating subsequence from a sequence ofindependent observations from a continuous distribution, and we prove a central limit theorem for the number of selections made by that policy. The proof exploits the backward recursion of dynamic programming and assembles a detailed understanding of the associated value functions and selection rules.

Duke Scholars

Author Alessandro Arlotto Fuqua School of Business