10th World Congress in Probability and Statistics
Organized Contributed Session (live Q&A at Track 3, 10:30PM KST)
Sequential Analysis and Applications (Organizer: Alexander Tartakovsky)
Asymptotically optimal control of FDR and related metrics for sequential multiple testing
Jay Bartroff (University of Southern California)
Nearly optimal sequential detection of signals in correlated Gaussian noise
Grigory Sokolov (Xavier University)
To this end we examine three procedures: (i) an adaptive version of the sequential probability ratio test (SPRT) built upon one-stage delayed estimators of the unknown signal intensity; (ii) the generalized SPRT; and (iii) the non-adaptive double SPRT (2-SPRT). The generalized SPRT has certain drawbacks in selecting thresholds to guarantee the upper bounds on error probabilities, but may appear to be slightly more efficient than the adaptive SPRT.
However, simulations show that the loss in performance of the adaptive SPRT compared to the generalized SPRT is very minor, so—coupled with the error probability guarantee—the adaptive SPRT can be recommended for practical applications.
And although the non-adaptive 2-SPRT is not asymptotically optimal for all signal strength values, it does offer benefits at the worst point in the indifference zone.
Acknowledgement: The work of Alexander Tartakovsky was supported in part by the Russian Science Foundation Grant 18-19-00452 at the Moscow Institute of Physics and Technology.
A unified approach for solving sequential selection problems
Yaakov Malinovsky (University of Maryland)
Sequential change detection by optimal weighted l2 divergence
Yao Xie (Georgia Institute of Technology)
Detection of temporary disorders
Michael Baron (American University)
Q&A for Organized Contributed Session 29
Alexander Tartakovsky (Moscow Institute of Physics and Technology )