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

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

confidence intervalsempirical Bayesfiducial inferencenonparametric deconvolution

Yifan Cui、Jan Hannig

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Center for Data Science,Zhejiang University,Hangzhou 310058,China

Department of Statistics and Operations Research,University of North Carolina at Chapel Hill,Chapel Hill,NC 27599,USA

2024

中国科学:数学(英文版)
中国科学院

中国科学:数学(英文版)

CSTPCD
影响因子:0.36
ISSN:1674-7283
年,卷(期):2024.67(11)