scalefree network Sample Clauses

scalefree network. To further evaluate the performance of our proposed method, we conduct another more complicated simulation study. In this simulation study, we generate 50 datasets with sample size 200 for scalefree network with dimension 1,000. In this simulation, we consider different network structure and different coefficients for each dataset. For each dataset, we randomly generate a scalefree network with dimension 1,000. Covariates X are generated from a multivariate Gaussian distribution X ∼ N(0, 0.3D), where D is the shortest path distance matrix between nodes in the generated scalefree Table 2.1: Simulation results for linear regression. PMSE: prediction mean squared error. TP: true positives, FP: false positives. Numbers of true network markers in Type 1 and Type 2 are 22 and 12, respectively. Method PMSE TP FP AUC PMSE TP FP AUC Simulation 1 Type 1 p = 33 Simulation 1 Type 1 p = 110 Lasso 52.3(1.6) 20.6(0.2) 7.3(0.3) 0.861(0.007) 71.6(1.9) 17.2(0.3) 19.6(1.2) 0.847(0.005) Elastic-net 50.9(1.4) 21.8(0.1) 10.4(0.2) 0.847(0.007) 73.7(1.8) 19.6(0.3) 46.6(2.9) 0.871(0.004) Grace 56.8(1.5) 21.6(0.1) 10.1(0.2) 0.864(0.007) 87.5(2.0) 17.9(0.4) 37.5(2.5) 0.897(0.004) aGrace 53.7(1.5) 22.0(0.0) 10.7(0.1) 0.875(0.007) 76.4(2.1) 20.6(0.3) 65.9(3.6) 0.899(0.005) L∞ 51.4(1.5) 21.8(0.1) 8.9(0.4) 0.970(0.006) 66.5(1.7) 21.5(0.2) 22.7(1.5) 0.973(0.005) aL∞ 54.2(1.3) 21.8(0.1) 8.2(0.6) 0.669(0.034) 63.5(1.5) 21.5(0.2) 19.6(1.4) 0.946(0.010) TTLP 54.3(1.6) 21.9(0.0) 10.1(0.4) 0.834(0.019) 72.6(2.0) 20.9(0.4) 44.2(4.6) 0.920(0.004) LTLP 51.3(1.2) 22.0(0.0) 8.8(0.6) 0.933(0.005) 67.1(1.7) 21.5(0.2) 57.6(2.7) 0.897(0.009) BRGL 51.0(1.3) 19.5(0.2) 4.1(0.3) 0.883(0.008) 79.7(1.8) 17.9(0.2) 22.1(0.9) 0.867(0.006) Ising(b=7) 54.9(3.0) 19.7(0.7) 2.9(0.7) 0.925(0.017) 94.9(5.9) 15.1(0.9) 33.9(2.4) 0.786(0.023) x XXXX (x ∼ X{0xx , x0 Xx)) 50.1(1.3) 21.9(0.1) 10.7(0.2) 0.863(0.010) 81.4(2.1) 14.8(0.5) 22.6(2.6) 0.779(0.009) TGLG (ε = 10−5) 45.2(1.2) 22.0(0.0) 2.2(0.6) 0.912(0.032) 63.9(2.8) 19.7(0.4) 17.8(2.9) 0.899(0.016) TGLG (logε ∼ N (−5, 9)) 46.0(1.3) 21.9(0.1) 1.7(0.5) 0.968(0.016) 74.1(2.4) 17.1(0.5) 19.3(2.7) 0.847(0.013) Simulation 1 Type 2 p = 33 Simulation 1 Type 2 p = 110 Lasso 23.1(0.6) 11.7(0.1) 11.8(0.6) 0.904(0.007) 30.6(0.8) 9.5(0.2) 19.1(1.1) 0.874(0.007) Elastic-net 23.4(0.6) 11.8(0.1) 15.4(0.6) 0.809(0.006) 31.4(0.9) 10.6(0.2) 34.0(2.1) 0.842(0.006) Grace 25.8(0.6) 11.4(0.1) 14.7(0.6) 0.813(0.005) 35.2(0.8) 9.1(0.2) 25.8(1.9) 0.855(0.005) aGrace 25.9(0.7) 12.0(0.0) 20.3(...
Sample 1
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