The proposed hierarchical Beta (Polya tree) posterior mean achieves lower mean squared error than MLE, Lasso, ridge, and adjusted MLE in three simulated high-dimensional logistic regression settings.
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Nonparametric Shrinkage Estimation in High Dimensional Generalized Linear Models via Polya Trees
The proposed hierarchical Beta (Polya tree) posterior mean achieves lower mean squared error than MLE, Lasso, ridge, and adjusted MLE in three simulated high-dimensional logistic regression settings.