Article ID: | iaor201526051 |
Volume: | 76 |
Issue: | 5 |
Start Page Number: | 809 |
End Page Number: | 825 |
Publication Date: | May 2015 |
Journal: | Automation and Remote Control |
Authors: | Juditsky A, Nemirovski A |
Keywords: | optimization, testing, programming: convex |
We propose a new approach to sequential testing which is an adaptive (on‐line) extension of the (off‐line) framework developed in [1]. It relies upon testing of pairs of hypotheses in the case where each hypothesis states that the vector of parameters underlying the distribution of observations belongs to a convex set. The nearly optimal under appropriate conditions test is yielded by a solution to an efficiently solvable convex optimization problem. The proposed methodology can be seen as a computationally friendly reformulation of the classical sequential testing.