Correlation in a Bayesian framework
نویسندگان
چکیده
The authors consider the correlation between two arbitrary functions of the data and a parameter, when the latter is regarded as a random variable with given prior distribution. They show how to compute such a correlation and use closed form expressions to assess the dependence between parameters and various classical or robust estimators thereof, as well as between p-values and posterior probabilities of the null hypothesis in the one-sided testing problem. Other applications involve the Dirichlet process and stationary Gaussian processes. Using this approach, the authors also derive a general nonparametric upper bound on Bayes risks.
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