Prior Elicitation, Variable Selection and Bayesian Computation for Logistic Regression Models
Logistic 回归模型的先验 elicitation、变量选择与贝叶斯计算
Summary Bayesian selection of variables is often difficult to carry out because of the challenge in specifying prior distributions for the regression parameters for all possible models, specifying a prior distribution on the model space and computations. We address these three issues for the logistic regression model. For the first, we propose an informative prior distribution for variable selection. Several theoretical and computational properties of the prior are derived…