Wuhan University Journal of Natural Sciences

, Volume 18, Issue 6, pp 466–470 | Cite as

Two-sided Empirical Bayes test for the exponential family with contaminated data

  • Jiaqing Chen
  • Qianyu Jin
  • Zhiqiang Chen
  • Cihua Liu


In this study, the two-sided Empirical Bayes test (EBT) rules for the parameter of continuous one-parameter exponential family with contaminated data (errors in variables) are constructed by a deconvolution kernel method. The asymptotically optimal uniformly over a class of prior distributions and uniform rates of convergence, which depends on two types of the error distributions for the proposed EBT rules, are obtained under suitable conditions. Finally, an example about the main results of this paper is given.

Key words

empirical Bayes test asymptotic optimal convergence rate contaminated data 

CLC number

O 212.1 


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Copyright information

© Wuhan University and Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Jiaqing Chen
    • 1
  • Qianyu Jin
    • 1
  • Zhiqiang Chen
    • 1
  • Cihua Liu
    • 2
  1. 1.College of ScienceWuhan University of TechnologyWuhanHubei, China
  2. 2.College of Mathematics and StatisticsHuazhong University of Science and TechnologyWuhanHubei, China

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