Asymptotically optimal multistage tests of simple hypotheses
Statistics Theory
2009-09-29 v1 Statistics Theory
Abstract
A family of variable stage size multistage tests of simple hypotheses is described, based on efficient multistage sampling procedures. Using a loss function that is a linear combination of sampling costs and error probabilities, these tests are shown to minimize the integrated risk to second order as the costs per stage and per observation approach zero. A numerical study shows significant improvement over group sequential tests in a binomial testing problem.
Cite
@article{arxiv.0712.0721,
title = {Asymptotically optimal multistage tests of simple hypotheses},
author = {Jay Bartroff},
journal= {arXiv preprint arXiv:0712.0721},
year = {2009}
}
Comments
Published in at http://dx.doi.org/10.1214/009053607000000235 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)