Calibrating general posterior credible regions

Nicholas Syring and Ryan Martin

Biometrika, 2019, vol. 106, issue 2, 479-486

Abstract: SummaryCalibration of credible regions derived from under- or misspecified models is an important and challenging problem. In this paper, we introduce a scalar tuning parameter that controls the posterior distribution spread, and develop a Monte Carlo algorithm that sets this parameter so that the corresponding credible region achieves the nominal frequentist coverage probability.

Keywords: Bootstrap; Coverage probability; Gibbs posterior distribution; Model misspecification; Stochastic approximation (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:oup:biomet:v:106:y:2019:i:2:p:479-486.

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