A new, nonparametric, approach to Bayesian robustness is presented. Whereas many studies in Bayesian robustness have dealt with a parametric sampling distribution, considering classes of prior distributions on the parameters, here we assume that the sampling distribution comes from a Dirichlet process with a parameter = , with > 0 and being a probability measure, specied with uncertainty.
Nonparametric Bayesian robustness
F Ruggeri
2010
Abstract
A new, nonparametric, approach to Bayesian robustness is presented. Whereas many studies in Bayesian robustness have dealt with a parametric sampling distribution, considering classes of prior distributions on the parameters, here we assume that the sampling distribution comes from a Dirichlet process with a parameter = , with > 0 and being a probability measure, specied with uncertainty.File in questo prodotto:
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