ANOVA summary of the impact of the importance sampling variants on the time p=0.050 Df Sum Sq Mean Sq F value Pr(>F) is.type 4 59.629 14.907 733.16 < 2.2e-16 *** Residuals 245 4.982 0.020 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$is.type ub gb sb wb gb < 2e-16 - - - sb < 2e-16 < 2e-16 - - wb < 2e-16 < 2e-16 1.3e-09 - pb < 2e-16 < 2e-16 < 2e-16 < 2e-16 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$is.type ub gb sb wb gb 7.8e-09 - - - sb 7.8e-09 7.8e-09 - - wb 7.8e-09 7.8e-09 7.8e-09 - pb 7.8e-09 7.8e-09 7.8e-09 7.8e-09 P value adjustment method: holm p=0.075 Df Sum Sq Mean Sq F value Pr(>F) is.type 4 17.7488 4.4372 405.74 < 2.2e-16 *** Residuals 245 2.6793 0.0109 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$is.type ub gb sb wb gb < 2e-16 - - - sb < 2e-16 < 2e-16 - - wb < 2e-16 < 2e-16 4.6e-05 - pb 4.6e-10 < 2e-16 < 2e-16 5.5e-15 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$is.type ub gb sb wb gb 7.8e-09 - - - sb 7.8e-09 7.8e-09 - - wb 7.8e-09 7.8e-09 0.00012 - pb 1.4e-07 7.8e-09 7.8e-09 7.8e-09 P value adjustment method: holm p=0.100 Df Sum Sq Mean Sq F value Pr(>F) is.type 4 4.3882 1.0970 466.64 < 2.2e-16 *** Residuals 245 0.5760 0.0024 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$is.type ub gb sb wb gb < 2e-16 - - - sb < 2e-16 < 2e-16 - - wb 5.7e-12 < 2e-16 3.6e-06 - pb 0.00059 < 2e-16 1.7e-13 2.8e-08 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$is.type ub gb sb wb gb 7.8e-09 - - - sb 7.8e-09 7.8e-09 - - wb 3.1e-08 7.8e-09 1.6e-05 - pb 0.00081 7.8e-09 7.8e-09 1.5e-06 P value adjustment method: holm p=0.125 Df Sum Sq Mean Sq F value Pr(>F) is.type 4 1.46247 0.36562 292.41 < 2.2e-16 *** Residuals 245 0.30634 0.00125 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$is.type ub gb sb wb gb < 2e-16 - - - sb 4.5e-14 < 2e-16 - - wb 2.8e-10 < 2e-16 0.00464 - pb 0.00032 < 2e-16 8.6e-09 0.00041 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$is.type ub gb sb wb gb 7.8e-09 - - - sb 3.3e-08 7.8e-09 - - wb 1.4e-07 7.8e-09 0.0055 - pb 6.8e-05 7.8e-09 5.7e-07 0.0011 P value adjustment method: holm p=0.150 Df Sum Sq Mean Sq F value Pr(>F) is.type 4 0.84892 0.21223 153.17 < 2.2e-16 *** Residuals 245 0.33947 0.00139 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$is.type ub gb sb wb gb < 2e-16 - - - sb 4.7e-09 < 2e-16 - - wb 1.1e-09 < 2e-16 0.63 - pb 1.9e-07 < 2e-16 0.39 0.63 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$is.type ub gb sb wb gb 7.8e-09 - - - sb 5.2e-07 7.8e-09 - - wb 1.9e-07 7.8e-09 0.83 - pb 1.5e-06 7.8e-09 0.28 0.83 P value adjustment method: holm p=0.175 Df Sum Sq Mean Sq F value Pr(>F) is.type 4 0.49839 0.12460 121.58 < 2.2e-16 *** Residuals 245 0.25109 0.00102 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$is.type ub gb sb wb gb < 2e-16 - - - sb 1.9e-08 < 2e-16 - - wb 2.4e-10 < 2e-16 0.390 - pb 1.0e-12 < 2e-16 0.024 0.048 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$is.type ub gb sb wb gb 7.8e-09 - - - sb 6.7e-07 7.8e-09 - - wb 7.7e-08 7.8e-09 0.354 - pb 2.2e-08 7.8e-09 0.028 0.050 P value adjustment method: holm p=0.200 Df Sum Sq Mean Sq F value Pr(>F) is.type 4 0.296027 0.074007 105.15 < 2.2e-16 *** Residuals 245 0.172442 0.000704 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$is.type ub gb sb wb gb < 2e-16 - - - sb 1.2e-08 < 2e-16 - - wb 4.1e-07 < 2e-16 0.88769 - pb 6.6e-16 < 2e-16 9.1e-05 0.00012 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$is.type ub gb sb wb gb 7.8e-09 - - - sb 2.1e-07 7.8e-09 - - wb 3.6e-06 7.8e-09 0.77212 - pb 7.8e-09 7.8e-09 8.8e-05 0.00010 P value adjustment method: holm p=0.300 Df Sum Sq Mean Sq F value Pr(>F) is.type 4 0.054546 0.013637 24.274 < 2.2e-16 *** Residuals 245 0.137637 0.000562 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$is.type ub gb sb wb gb < 2e-16 - - - sb 0.32 < 2e-16 - - wb 0.32 < 2e-16 0.32 - pb 2.3e-06 1.2e-10 5.1e-05 6.3e-06 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$is.type ub gb sb wb gb 7.8e-09 - - - sb 0.41 7.8e-09 - - wb 0.41 7.8e-09 0.41 - pb 8.7e-06 2.0e-07 8.6e-05 1.6e-05 P value adjustment method: holm p=0.400 Df Sum Sq Mean Sq F value Pr(>F) is.type 4 0.028556 0.007139 12.568 2.572e-09 *** Residuals 245 0.139172 0.000568 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Pairwise comparisons using t tests with non-pooled SD data: currentDataAnova$run.time and currentDataAnova$is.type ub gb sb wb gb < 2e-16 - - - sb 1.00000 9.6e-14 - - wb 1.00000 2.5e-14 0.20325 - pb 0.00162 1.8e-07 0.00127 0.00017 P value adjustment method: holm Pairwise comparisons using Wilcoxon rank sum test data: currentDataAnova$run.time and currentDataAnova$is.type ub gb sb wb gb 7.8e-09 - - - sb 1.0000 3.5e-08 - - wb 1.0000 2.3e-08 0.1243 - pb 0.0024 3.1e-06 0.0013 0.0006 P value adjustment method: holm