Simulations for Case II, training sample size = 100, test sample size = 100.

BVS-SL(κ) represents the Bayes variable selection with belief parameter κ for all edges. Pencred, SSVS, Lasso, EL, SCAD, SSL, and Flasso represent the penalized joint credible regions approach, stochastic search variable selection, L1 penalized regression, and elastic net, the smooth clipped absolute deviation, the spike and slab lasso, and sparse fused lasso respectively. MSPE: out of sample predictive MSE; Pwr(10% FDR) is sensitivity controlling for 90% specificity; MS: estimated model size; FP: false positives, and Cov95 is coverage under 95% predictive intervals. The true model size is 10.