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• W2064505280 abstract "This article reviews Bayesian inference from the perspective that the designated model is misspecified. This misspecification has implications in interpretation of objects, such as the prior distribution, which has been the cause of recent questioning of the appropriateness of Bayesian inference in this scenario. The main focus of this article is to establish the suitability of applying the Bayes update to a misspecified model, and relies on representation theorems for sequences of symmetric distributions; the identification of parameter values of interest; and the construction of sequences of distributions which act as the guesses as to where the next observation is coming from. A conclusion is that a clear identification of the fundamental starting point for the Bayesian is described." @default.
• W2064505280 created "2016-06-24" @default.
• W2064505280 creator A5037434634 @default.
• W2064505280 date "2013-10-01" @default.
• W2064505280 modified "2023-09-25" @default.
• W2064505280 title "Bayesian inference with misspecified models" @default.
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• W2064505280 doi "https://doi.org/10.1016/j.jspi.2013.05.013" @default.
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