Reputations changeable, situations tolerable
Statistical Modeling, Causal Inference, and Social Science 2013-05-15
Summary:
David Kessler, Peter Hoff, and David Dunson write: Marginally specified priors for nonparametric Bayesian estimation Prior specification for nonparametric Bayesian inference involves the difficult task of quantifying prior knowledge about a parameter of high, often infinite, dimension. Realistically, a statistician is unlikely to have informed opinions about all aspects of such a parameter, but may [...]
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