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Robust Empirical Bayes Confidence Intervals

v1.0.0 · Sep 6, 2021 · MIT + file LICENSE
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Description

Computes empirical Bayes confidence estimators and confidence intervals in a normal means model. The intervals are robust in the sense that they achieve correct coverage regardless of the distribution of the means. If the means are treated as fixed, the intervals have an average coverage guarantee. The implementation is based on Armstrong, Kolesár and Plagborg-Møller (2020) <arXiv:2004.03448>.

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CRAN incoming feasibility

Maintainer: ‘Michal Kolesár <kolesarmi@googlemail.com>’

The Description field contains
  and Plagborg-Møller (2020) <arXiv:2004.03448>.
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.
NOTE r-devel-linux-x86_64-debian-gcc

CRAN incoming feasibility

Maintainer: ‘Michal Kolesár <kolesarmi@googlemail.com>’

The Description field contains
  and Plagborg-Møller (2020) <arXiv:2004.03448>.
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.
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                12 OK ·                 2 NOTE ·                 0 WARNING ·                 0 ERROR ·                 0 FAILURE              
              Mar 9, 2026
            
            

              

                

                  NOTE
                  r-devel-linux-x86_64-debian-clang
                

                
CRAN incoming feasibility

                
Maintainer: ‘Michal Kolesár <kolesarmi@googlemail.com>’

The Description field contains
  and Plagborg-Møller (2020) <arXiv:2004.03448>.
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.

              

              

                

                  NOTE
                  r-devel-linux-x86_64-debian-gcc
                

                
CRAN incoming feasibility

                
Maintainer: ‘Michal Kolesár <kolesarmi@googlemail.com>’

The Description field contains
  and Plagborg-Møller (2020) <arXiv:2004.03448>.
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.

              

            

          

        

      


      

      

      
      

        
Version History

        

          

            new
            1.0.0
            Mar 9, 2026