The problem of low counts in a signal plus noise model
成果类型：
Article
署名作者：
Woodroofe, M; Wang, HY
署名单位：
University of Michigan System; University of Michigan; Academia Sinica - Taiwan
刊物名称：
ANNALS OF STATISTICS
ISSN/ISSBN：
0090-5364
发表日期：
2000
页码：
1561-1569
关键词：
摘要：
Consider the model X = B + S, where B and S are independent Poisson random variables with means mu and upsilon, upsilon is unknown, but mu is known. The model arises in particle physics and some recent articles have suggested conditioning on the observed bound on B; that is, if X = n is observed, then the suggestion is to base inference on the conditional distribution of X given B less than or equal to n. This conditioning is non-standard in that it does not correspond to a partition of the sample space. It is examined here from the view point of decision theory and shown to lead to admissible formal Bayes procedures.