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Table 6 Computation time

From: A fast least-squares algorithm for population inference

K N Α AD LS FRAPPE Significance LSα
2 100 0.10 4.71 1.00 9.97 LS < AD < FR 0.77
2 100 0.50 4.69 1.16 8.22 LS < AD < FR 1.12
2 100 1.00 5.46 1.78 8.31 LS < AD < FR 1.77
2 100 2.00 6.25 2.37 10.40 LS < AD < FR 2.55
2 1000 0.10 43.37 11.87 136.88 LS < AD < FR 8.06
2 1000 0.50 51.70 13.98 112.41 LS < AD < FR 12.34
2 1000 1.00 62.00 24.43 118.90 LS < AD < FR 24.03
2 1000 2.00 83.07 51.33 195.43 LS < AD < FR 48.43
2 10000 0.10 447.68 142.14 1963.83 LS < AD < FR 93.61
2 10000 0.50 570.12 209.39 1908.72 LS < AD < FR 157.44
2 10000 1.00 687.88 352.24 2242.18 LS < AD < FR 349.51
2 10000 2.00 1037.45 796.83 3762.70 LS < AD < FR 406.63
3 100 0.10 6.10 1.84 15.29 LS < AD < FR 1.48
3 100 0.50 6.42 2.05 15.75 LS < AD < FR 1.90
3 100 1.00 7.19 2.71 16.78 LS < AD < FR 2.74
3 100 2.00 9.00 4.01 19.80 LS < AD < FR 4.24
3 1000 0.10 69.41 18.32 223.32 LS < AD < FR 12.53
3 1000 0.50 78.73 24.10 264.85 LS < AD < FR 21.42
3 1000 1.00 96.89 38.06 305.50 LS < AD < FR 36.63
3 1000 2.00 121.45 60.79 355.51 LS < AD < FR 55.54
3 10000 0.10 791.36 155.56 3256.83 LS < AD < FR 121.19
3 10000 0.50 883.99 301.52 4251.68 LS < AD < FR 264.77
3 10000 1.00 1175.25 617.80 5111.92 LS < AD < FR 578.42
3 10000 2.00 1506.20 1404.27 7052.33 LS < AD < FR 901.56
4 100 0.10 8.06 2.45 23.93 LS < AD < FR 2.00
4 100 0.50 8.78 2.66 26.56 LS < AD < FR 2.72
4 100 1.00 10.03 3.70 30.89 LS < AD < FR 3.43
4 100 2.00 12.94 5.00 37.26 LS < AD < FR 4.86
4 1000 0.10 81.72 17.32 386.11 LS < AD < FR 13.45
4 1000 0.50 99.92 24.37 433.17 LS < AD < FR 22.68
4 1000 1.00 117.71 36.94 508.49 LS < AD < FR 36.01
4 1000 2.00 156.39 58.02 564.57 LS < AD < FR 57.62
4 10000 0.10 879.95 229.06 5798.15 LS < AD < FR 176.27
4 10000 0.50 1170.97 480.99 7051.69 LS < AD < FR 505.45
4 10000 1.00 1555.90 1017.41 8108.08 LS < AD < FR 1051.81
4 10000 2.00 2202.08 2538.54 10445.75 AD = LS < FR 1308.79
  1. ‘AD’ = Admixture with ε = MN×10-4, ‘LS1’ = Least-squares with ε = MN×10-4 and α = 1, ‘FR’ = FRAPPE with ε = 1. Bold values indicate significantly less error than those without bold. ‘<’ indicates significantly less at 4.6e-4 level, and ‘=’ indicates insignificant difference. ‘LSα’ = Least-squares with correct α provided only for reference.