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On priors which give Bayes minimax estimators of Baranchik’s form

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  • Stein Estimation and Statistical Shrinkage Methods
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Abstract

We study the construction of prior distributions which give Bayes minimax estimators of a normal mean vector. Particular attention is paid to priors which are not scale mixtures of normal distributions.

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References

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Acknowledgements

Strawderman’s research was partially supported by a Simons Foundation grant (#418098). Wells’s research was partially supported by NIH grants R01 GM135926 and P01 AI159402-01. There are no conflicts of interest.

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Authors and Affiliations

  1. Normandie University, UNIROUEN, UNIHAVRE, INSA Rouen, LITIS, Avenue de l’Université, BP 12, 76801, Saint-Étienne-du-Rouvray, France

    Dominique Fourdrinier

  2. Department of Statistics, Rutgers University, 561 Hill Center, Busch Campus, Piscataway, NJ, 08854-8019, USA

    William E. Strawderman

  3. Department of Statistics and Data Science, Cornell University, 1190 Comstock Hall, Ithaca, NY, 14853, USA

    Martin T. Wells

Authors
  1. Dominique Fourdrinier
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  2. William E. Strawderman
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  3. Martin T. Wells
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Correspondence to Martin T. Wells.

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Fourdrinier, D., Strawderman, W.E. & Wells, M.T. On priors which give Bayes minimax estimators of Baranchik’s form. Jpn J Stat Data Sci (2023). https://doi.org/10.1007/s42081-023-00198-y

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  • DOI: https://doi.org/10.1007/s42081-023-00198-y

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