A fiducial approach to the nonparametric deconvolution problem:The discrete case

作     者：Yifan Cui Jan Hannig 

作者机构：Center for Data ScienceZhejiang UniversityHangzhou 310058China Department of Statistics and Operations ResearchUniversity of North Carolina at Chapel HillChapel HillNC 27599USA 

出 版 物：《Science China Mathematics》 (中国科学（数学英文版）)

年 卷 期：2024年第67卷第11期

页      面：2653-2670页

核心收录：

学科分类：02[经济学] 0202[经济学-应用经济学] 020208[经济学-统计学] 07[理学] 0714[理学-统计学（可授理学、经济学学位）] 070103[理学-概率论与数理统计] 0701[理学-数学] 

基　　金：supported by National Natural Science Foundation of China(Grant No.U23A2064) Singapore Ministry of Education U.S.National Institute of Health U.S.National Science Foundation 

主　　题：confidence intervals empirical Bayes fiducial inference nonparametric deconvolution 

摘      要：Fiducial inference is applied to nonparametric g-modeling in the discrete *** propose a computationally efficient algorithm to sample from the fiducial distribution and use the generated samples to construct point estimates and confidence *** study the theoretical properties of the fiducial distribution and perform extensive simulations in various *** proposed approach gives rise to good statistical performance in terms of the mean squared error of point estimators and coverage of confidence ***,we apply the proposed fiducial method to estimate the probability of each satellite site being malignant using gastric adenocarcinoma data with 844 patients.