Nearly Minimax One-Sided Mixture-Based Sequential Tests

Details Nearly Minimax One-Sided Mixture-Based Sequential Tests Nearly Minimax One-Sided Mixture-Based Sequential Tests

2011-10-05

arxiv.org/abs/1110.0902v2

Mathematics

Statistics Theory

25 pages

Scientific paper

We focus on one-sided, mixture-based stopping rules for the problem of sequential testing a simple null hypothesis against a composite alternative. For the latter, we consider two cases---either a discrete alternative or a continuous alternative that can be embedded into an exponential family. For each case, we find a mixture-based stopping rule that is nearly minimax in the sense of minimizing the maximal Kullback-Leibler information. The proof of this result is based on finding an almost Bayes rule for an appropriate sequential decision problem and on high-order asymptotic approximations for the performance characteristics of arbitrary mixture-based stopping times. We also evaluate the asymptotic performance loss of certain intuitive mixture rules and verify the accuracy of our asymptotic approximations with simulation experiments.

Affiliated with

Also associated with

No associations

Rating

Nearly Minimax One-Sided Mixture-Based Sequential Tests does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Nearly Minimax One-Sided Mixture-Based Sequential Tests, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Nearly Minimax One-Sided Mixture-Based Sequential Tests will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-324676