Frequentist Standard Errors of Bayes Estimators. Academic Article uri icon

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 (MCMC) 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.

published proceedings

  • Comput Stat

author list (cited authors)

  • Lee, D., Carroll, R. J., & Sinha, S.

citation count

  • 1

complete list of authors

  • Lee, DongHyuk||Carroll, Raymond J||Sinha, Samiran

publication date

  • September 2017