TABLE 4

Estimates of the average coefficient of dominance (± standard error) for a model where h follows a uniform distribution between 0 and exp(−ks), with mean Embedded Image or 0.2

Methodλ = 0.2, = 0.02,
 β = 2λ = 0.2, = 0.02,
 β = 1.01λ = 0.006, = 0.2,
 β = 1.01λ = 0.006, = 0.2,
 β = 1.01
N0.4 0.4 0.4 0.2
r−0.25−0.32−0.32−0.58
Embedded ImageSIM 1030.31 ± 0.0060.36 ± 0.0040.34 ± 0.0200.22 ± 0.021
DA 1030.31 ± 0.0040.37 ± 0.0040.32 ± 0.0080.25 ± 0.012
DA 1050.19 ± 0.0050.27 ± 0.0170.20 ± 0.0200.17 ± 0.024
DA 1070.13 ± 0.0100.24 ± 0.0160.18 ± 0.0160.08 ± 0.008
N(1/s)0.000.000.000.00
by.xSIM 1030.25 ± 0.003 (0.25)0.21 ± 0.003 (0.21)0.14 ± 0.007 (0.19)0.02 ± 0.002 (0.07)
DA 1030.25 ± 0.002 (0.25)0.22 ± 0.004 (0.22)0.15 ± 0.005 (0.20)0.02 ± 0.001 (0.07)
DA 1050.10 ± 0.004 (no QN)0.12 ± 0.004 (0.12)0.08 ± 0.006 (0.11)0.00 ± 0.000 (0.03)
DA 1070.09 ± 0.005 (no QN)0.08 ± 0.005 (0.08)0.06 ± 0.004 (0.09)0.00 ± 0.000 (0.02)
N(s)0.000.000.000.00
Embedded ImageSIM 1030.32 ± 0.0030.32 ± 0.0020.21 ± 0.0060.06 ± 0.003
DA 1030.32 ± 0.0020.32 ± 0.0010.22 ± 0.0050.07 ± 0.001
DA 1050.23 ± 0.0010.23 ± 0.0020.13 ± 0.0050.02 ± 0.001
DA 1070.19 ± 0.0040.19 ± 0.0020.09 ± 0.0050.01 ± 0.000
N0.000.000.000.00
1/bx.ySIM 1030.43 ± 0.004 (0.51)0.39 ± 0.003 (0.49)0.29 ± 0.012 (0.37)0.33 ± 0.029 (0.24)
DA 1030.42 ± 0.002 (0.50)0.39 ± 0.002 (0.48)0.32 ± 0.005 (0.38)0.32 ± 0.011 (0.24)
DA 1050.37 ± 0.002 (no QN)0.33 ± 0.003 (no QN)0.27 ± 0.007 (0.35)0.38 ± 0.164 (0.16)
DA 1070.37 ± 0.004 (no QN)0.33 ± 0.005 (no QN)0.29 ± 0.009 (0.36)0.08 ± 0.075 (0.18)
NEmbedded Image0.360.320.320.08
  • The variance of h is Embedded Image. The correlation between s and h (r) is given in the table. Parameters and definitions are as in Table 2.