We address the question as to whether a prior distribution on the space of distribution functions exists which generates the posterior produced by Efron's and Rubin's bootstrap techniques, emphasizing the connections with the Dirichlet process. We also introduce a new resampling plan which has two advantages: prior opinions are taken into account and the predictive distribution of the future observations is not forced to be concentrated on observed values.
Bayesian nonparametric predictive inference and bootstrap techniques
MULIERE, PIETRO;
1996
Abstract
We address the question as to whether a prior distribution on the space of distribution functions exists which generates the posterior produced by Efron's and Rubin's bootstrap techniques, emphasizing the connections with the Dirichlet process. We also introduce a new resampling plan which has two advantages: prior opinions are taken into account and the predictive distribution of the future observations is not forced to be concentrated on observed values.File in questo prodotto:
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