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Frequentist standard errors of Bayes estimators

Author

Listed:
  • DongHyuk Lee

    (Texas A&M University)

  • Raymond J. Carroll

    (Texas A&M University
    University of Technology Sydney)

  • Samiran Sinha

    (Texas A&M University)

Abstract

Frequentist standard errors are a measure of uncertainty of an estimator, and the basis for statistical inferences. Frequestist standard errors can also be derived for Bayes estimators. However, except in special cases, the computation of the standard error of Bayesian estimators requires bootstrapping, which in combination with Markov chain Monte Carlo can be highly time consuming. We discuss an alternative approach for computing frequentist standard errors of Bayesian estimators, including importance sampling. Through several numerical examples we show that our approach can be much more computationally efficient than the standard bootstrap.

Suggested Citation

  • DongHyuk Lee & Raymond J. Carroll & Samiran Sinha, 2017. "Frequentist standard errors of Bayes estimators," Computational Statistics, Springer, vol. 32(3), pages 867-888, September.
  • Handle: RePEc:spr:compst:v:32:y:2017:i:3:d:10.1007_s00180-017-0710-x
    DOI: 10.1007/s00180-017-0710-x
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    References listed on IDEAS

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    1. James Berger & Elías Moreno & Luis Pericchi & M. Bayarri & José Bernardo & Juan Cano & Julián Horra & Jacinto Martín & David Ríos-Insúa & Bruno Betrò & A. Dasgupta & Paul Gustafson & Larry Wasserman &, 1994. "An overview of robust Bayesian analysis," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 3(1), pages 5-124, June.
    2. Liang F., 2002. "Dynamically Weighted Importance Sampling in Monte Carlo Computation," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 807-821, September.
    3. Ni, Shawn & Sun, Dongchu & Sun, Xiaoqian, 2007. "Intrinsic Bayesian Estimation of Vector Autoregression Impulse Responses," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 163-176, April.
    4. Bradley Efron, 2015. "Frequentist accuracy of Bayesian estimates," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 77(3), pages 617-646, June.
    5. James H. Stock & Mark W. Watson, 2001. "Vector Autoregressions," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 101-115, Fall.
    6. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    7. Willems, Gert & Van Aelst, Stefan, 2005. "Fast and robust bootstrap for LTS," Computational Statistics & Data Analysis, Elsevier, vol. 48(4), pages 703-715, April.
    8. Hu, Feifang & Hu, Jianhua, 2000. "A note on breakdown theory for bootstrap methods," Statistics & Probability Letters, Elsevier, vol. 50(1), pages 49-53, October.
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