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Influence of the prior distribution on the risk of the Bayes rule

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Abstract

The risk influence function is defined as the directional derivative of the risk of the Bayes rule. The properties of this function are studied and the relationship between unimodal prior distribution and the shape of the frequentist risk of the corresponding Bayes procedure is examined.

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References

  1. Berger, J. (1984). The robust Bayesian viewpoint. J. B. Kadane, ed.,Robustness of Bayesian Analysis, Elsevier, Amsterdam.

    Google Scholar 

  2. Bickel, P. J. (1981). Minimax estimation of the mean of a normal distribution when the parameter space is restricted.Ann. Statist. 9, 1301–1309.

    Google Scholar 

  3. Brewster, J. F., and Zidek, J. V. (1974). Improving on equivariant estimators.Ann. Statist. 2, 21–38.

    Google Scholar 

  4. Brown, L. D. (1986).Fundamentals of Statistical Exponential Families with Applications in Statistical Decision Theory, Institute of Mathematical Statistics, Lecture Notes—Monograph Series, Volume 9, Hayward, California.

    Google Scholar 

  5. Casella, G., and Strawderman, W. E. (1981). Estimating a bounded normal mean.Ann. Statist. 9, 868–876.

    Google Scholar 

  6. DasGupta, A. (1985). Bayes minimax estimation in multiparameter families when the parameter space is restricted to a bounded conves set.Sankhya A 47, 326–332.

    Google Scholar 

  7. Dharmadhikari, S., and Joag-dev, K. (1988).Unimodality, Convexity, and Applications, Academic Press, San Diego.

    Google Scholar 

  8. Diaconis, P., and Freedman, D. (1986). On the consistency of Bayes estimates.Ann. Statist. 14, 1–67.

    Google Scholar 

  9. Diaconis, P., and Ylvisaker, D. (1979). Conjugate priors for exponential families.Ann. Statist. 7, 269–281.

    Google Scholar 

  10. Hampel, F. R., Ronchetti, E. M., Rouseeuw, P. J., and Stahel, W. A. (1986).Robust Statistics: The Approach Based on Influence Functions, Wiley, New York.

    Google Scholar 

  11. Huber, P. J. (1977). The use of Choquet capacities in statistics.Proc. 39th Session ISI, pp. 181–188.

  12. Hudson, H. M. (1978). A natural identity for exponential families with applications in multivariate estimation.Ann. Statist. 6, 473–484.

    Google Scholar 

  13. Isii, K., and Noda, K. (1985). A vector space approach for obtaining a condition for the admissibility of statistical decision functions, K. Matusita, ed.,Statistical Theory and Data Analysis, North Holland, Amsterdam.

    Google Scholar 

  14. Karlin, S. (1968).Total Positivity, Stanford University Press, Stanford, California.

    Google Scholar 

  15. Kempthorne, P. J. (1988). Dominating inadmissible procedures using compromise decision theory. S. S. Gupta and J. Berger, eds.,Statistical Decision Theory and Related Topics IV, Springer, New York.

    Google Scholar 

  16. Kozek, A. (1982). Towards a calculus of admissibility.Ann. Statist. 10, 825–837.

    Google Scholar 

  17. LeCam, L. (1955). An extension of Wald's theory of statistical decision functions.Ann. Math. Statist. 26, 69–81.

    Google Scholar 

  18. Polasek, W. (1986). Local sensitivity analysis and Bayesian regression diagnostics. P. Goel and A. Zellner, eds.,Bayesian Inference and Decision Techniques, Elsevier, N. Holland.

    Google Scholar 

  19. Rukhin, A. L. (1992). Asymptotic risk behavior of mean vector and variance estimators and the problem of positive normal mean.Ann. Inst. Statist. Math. 44, 299–311.

    Google Scholar 

  20. Wald, A. (1950).Statistical Decision Functions, Wiley, New York, New York.

    Google Scholar 

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Rukhin, A.L. Influence of the prior distribution on the risk of the Bayes rule. J Theor Probab 6, 71–87 (1993). https://doi.org/10.1007/BF01046769

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