Table 4.
Experiment | N | N′ (%) | minSQR | maxLKHD | ||
---|---|---|---|---|---|---|
KS | p2 () | KS | p1 () | |||
elder_gng | 2,348 | 2 (0.09) | 66.58 | 0.000 (28.92 ± 7.32) | 50.24 | 0.040 (30.98 ± 17.55) |
elder_hfgng | 1,174 | 8 (0.68) | 34.20 | 0.040 (20.67 ± 5.70) | 32.64 | 0.010 (20.66 ± 5.83) |
elder_hfyn | 1,175 | 2 (0.17) | 32.09 | 0.040 (20.01 ± 4.86) | 24.76 | 0.090 (19.22 ± 6.69) |
elder_lfgng | 1,174 | 1 (0.09) | 43.49 | 0.000 (21.47 ± 5.83) | 33.22 | 0.030 (20.57 ± 6.90) |
elder_lfyn | 1,139 | 4 (0.35) | 19.97 | 0.550 (20.55 ± 6.37) | 19.71 | 0.620 (19.97 ± 6.11) |
elder_pseudo | 1,910 | 5 (0.26) | 57.26 | 0.000 (26.91 ± 6.64) | 57.11 | 0.010 (26.61 ± 10.06) |
elder_yn | 2,314 | 5 (0.22) | 36.83 | 0.240 (28.57 ± 7.46) | 29.72 | 0.230 (30.54 ± 14.33) |
young_gng | 2,396 | 10 (0.42) | 38.93 | 0.250 (27.82 ± 6.32) | 43.11 | 0.020 (30.19 ± 17.07) |
young_hfgng | 1,200 | 8 (0.67) | 23.28 | 0.780 (19.25 ± 4.39) | 17.82 | 0.430 (18.07 ± 4.13) |
young_hfyn | 1,180 | 9 (0.76) | 27.97 | 0.050 (19.68 ± 4.91) | 28.93 | 0.010 (20.74 ± 7.71) |
young_lf | 1,196 | 5 (0.42) | 25.11 | 0.310 (20.09 ± 5.21) | 25.32 | 0.020 (19.69 ± 4.29) |
young_lfgng | 1,196 | 5 (0.42) | 25.11 | 0.280 (20.51 ± 5.08) | 25.32 | 0.080 (20.55 ± 5.05) |
young_lfyn | 1,132 | 3 (0.27) | 25.20 | 0.230 (19.42 ± 5.40) | 16.60 | 0.780 (20.72 ± 8.53) |
young_pseudo | 2,326 | 10 (0.43) | 23.33 | 0.940 (27.59 ± 7.05) | 25.85 | 0.870 (28.45 ± 12.48) |
young_yn | 2,312 | 12 (0.52) | 46.10 | 0.130 (27.80 ± 7.87) | 28.58 | 0.210 (31.21 ± 19.74) |
KS is the Kolmogorov-Smirnov statistic calculated between the data and its fitted ex-Gaussian. N is the number of data points in each empirical dataset, N′ in the number of points removed by the trimming and in brackets next to it its proportion in relation to the total data. In columns p1 and p2, one finds the probabilities that a randomly generated dataset has a bigger KS statistic than the empirical data. In parenthesis, the average KS statistic and standard deviation for the generated random samples.