Principles of Bayesian inference using general divergence criteria

Principles of Bayesian inference using general divergence criteria

When it is acknowledged that all candidate parameterised statistical models are misspecified relative to the data generating process, the decision maker (DM) must currently concern themselves with inference for the parameter value minimising the Kullback-Leibler (KL)-divergence between the model and...

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Bibliographic Details
Main Authors:	Jewson, J, Smith, J, Holmes, C
Format:	Journal article
Published:	MDPI 2018

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