A Symmetric Random Scan Collapsed Gibbs Sampler for Fully Bayesian Variable Selection with Spike-and-Slab Priors
对称随机扫描坍缩 Gibbs 抽样器:尖峰-平板先验下的全贝叶斯变量选择
We introduce a symmetric random scan Gibbs sampler for scalable Bayesian variable selection that eliminates storage of the full cross-product matrix by computing required quantities on-the-fly. Data-informed proposal weights, constructed from marginal correlations, concentrate sampling effort on promising candidates while a uniform mixing component ensures theoretical validity. We provide explicit guidance for selecting tuning parameters based on the ratio of signal to null…