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任意相依结构下的极小化p值合并(王彬)
2022-05-12 | 编辑:

  Methods of merging several p-values into a single p-value are important in their own right and widely used in multiple hypothesis testing. This paper is the first to systematically study the admissibility (in Wald’s sense) of p-merging functions and their domination structure, without any information on the dependence structure of the input p-values. As a technical tool, we use the notion of e-values, which are alternatives to p-values recently promoted by several authors. We obtain several results on the representation of admissible p-merging functions via e-values and on (in)admissibility of existing p-merging functions. By introducing new admissible p-merging functions, we show that some classic merging methods can be strictly improved to enhance power without compromising validity under arbitrary dependence. 

    

  Publication: 

  Annals of Statistics 50(1): 351-375 (February 2022) 

  

  Author: 

  Vladimir Vovk 

  Department of Computer Science, Royal Holloway, University of London, Egham, Surrey, UK. 

  E-mail: v.vovk@rhul.ac.uk  

    

  Bin Wang 

  RCSDS, NCMIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China. 

  E-mail: wangbin@amss.ac.cn  

    

  Ruodu Wang 

  Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, Ontario, Canada. 

  E-mail: wang@uwaterloo.ca  

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