Moment-Based Minimax Stopping Functions for Sequences of Random Variables
NOTE: At the time of publication, the author Theodore P. Hill was not yet affiliated with Cal Poly.
Minimax-optimal stopping times and minimax (worst-case) distributions are found for the problem of stopping a sequence of uniformly bounded independent random variables, when only the means and/or variances are known, in contrast to the classical setting where the complete joint distributions of the random variables are known. Results are obtained for both the independent and i.i.d. cases, with applications given to the problem of order section in optimal stopping.
Frans A. Boshuizen and Theodore P. Hill. "Moment-Based Minimax Stopping Functions for Sequences of Random Variables" Stochastic Processes and Their Applications 43.2 (1992): 303-316.
Available at: http://works.bepress.com/tphill/61