Bayesian Regression Using a Prior on the Model Fit: The R2-D2 Shrinkage Prior
基于模型拟合度先验的贝叶斯回归：R2-D2 收缩先验
Prior distributions for high-dimensional linear regression require specifying a joint distribution for the unobserved regression coefficients, which is inherently difficult. We instead propose a new class of shrinkage priors for linear regression via specifying a prior first on the model fit, in particular, the coefficient of determination, and then distributing through to the coefficients in a novel way. The proposed method compares favorably to previous approaches in terms…