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EFFECTS OF HYPERPARAMETERS IN A NORMAL MODEL WITH CONJUGATE PRIORDr. Susan AlberDepartment of Preventative and Social MedicineDate: Thursday 25 March 2010 Time: 11:00 a.m. Place: Room 241 (Science III) For a normal model with a conjugate prior, we investigate the effects of the hyperparameters on the long-run frequentist properties of posterior point and interval estimates. Under an assumed sampling model for the data generating mechanism, we develop two types of hyperpararameter optimality. Mean squared error (MSE) optimal
hyperparameters minimize the MSE of posterior point estimates. Credible interval optimal hyperparameters result in credible intervals that have minimum length while still retaining nominal coverage. We give an example to demonstrate how to use our results to guide the selection of hyperparameters. 00318171817
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