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What is Bayesian Bridge Estimator for Regression about?

This paper develops the Bayesian bridge estimator for regularized regression and classification. It proposes two key mixture representations for the Bayesian bridge model: a scale mixture of normals with respect to an alpha-stable random variable, and a mixture of Bartlett-Fejer kernels with respect to a two-component mixture of gamma random variables. Both lead to MCMC methods for posterior simulation. The paper finds the Bayesian bridge model outperforms classical estimators in prediction across simulated

Author

benmutaganda

Language

EN