2008/09/18 by Xinjia Chen, Chen, Xinjia · 2 citations
Computer Science · Engineering · Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Fluid Dynamics and Heat Transfer #Machine Learning (cs.LG) #Methodology (stat.ME) #Probability (math.PR) #Statistics Theory (math.ST) #cs.LG #math.PR #math.ST #stat.ME #stat.TH
paper · pdf · doi:10.48550/arxiv.0809.3170
77 pages, no figure; added more references; in Proceedings of SPIE Conferences, Orlando, Florida, April 5-10, 2010 and April 25-29, 2011
openalex publication_date 2008/09/18 · arxiv created 2012/12/05 · arxiv updated 2013/11/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this paper, we have established a general framework of multistage hypothesis tests which applies to arbitrarily many mutually exclusive and exhaustive composite hypotheses. Within the new framework, we have constructed specific multistage tests which rigorously control the risk of committing decision errors and are more efficient than previous tests in terms of average sample number and the number of sampling operations. Without truncation, the sample numbers of our testing plans are absolutely bounded.