Prior Near-Ignorance for Inferences in the k-parameter Exponential Family

  title={Prior Near-Ignorance for Inferences in the k-parameter Exponential Family},
  author={Alessio Benavoli and Marco Zaffalon},
This paper proposes a model of prior ignorance about a multivariate variable based on a set of distributions M . In particular, we discuss four minimal properties that a model of prior ignorance should satisfy: invariance, near-ignorance, learning and convergence. Near-ignorance and invariance ensure that our prior model behaves as a vacuous model with respect to some statistical inferences (e.g., mean, credible intervals, etc.) and some transformation of the parameter space. Learning and… CONTINUE READING
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