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Table 2.

Estimated mean parameter values for the bias functions corresponding to the respective magnitude cuts.

Sample id Magnitude range Cut β ρg ϵg
1 −21.5 ≤ K ≤ −21.0 K2M + + ≤ 11.5 0.35 0.65 0.98 0.28
2 11.5 <  K2M + + ≤ 12.5 0.31 0.74 1.06 0.26
3 −22.0 ≤ K ≤ −21.5 K2M + + ≤ 11.5 0.37 0.77 1.11 0.19
4 11.5 <  K2M + + ≤ 12.5 0.24 0.74 0.85 0.26
5 −22.5 ≤ K ≤ −22.0 K2M + + ≤ 11.5 0.25 0.75 0.91 0.27
6 11.5 <  K2M + + ≤ 12.5 0.40 0.79 1.30 0.12
7 −23.0 ≤ K ≤ −22.5 K2M + + ≤ 11.5 0.19 0.80 0.81 0.25
8 11.5 <  K2M + + ≤ 12.5 0.24 0.76 1.08 0.12
9 −23.5 ≤ K ≤ −23.0 K2M + + ≤ 11.5 0.16 0.79 0.97 0.20
10 11.5 <  K2M + + ≤ 12.5 0.28 0.73 1.33 0.07
11 −24.0 ≤ K ≤ −23.5 K2M + + ≤ 11.5 0.19 0.77 1.61 0.09
12 11.5 <  K2M + + ≤ 12.5 0.14 0.67 1.31 0.05
13 −24.5 ≤ K ≤ −24.0 K2M + + ≤ 11.5 0.05 0.83 1.23 0.11
14 11.5 <  K2M + + ≤ 12.5 0.04 0.51 0.97 0.085
15 −25.0 ≤ K ≤ −24.5 K2M + + ≤ 11.5 0.01 0.88 0.98 0.12
16 11.5 <  K2M + + ≤ 12.5 0.01 0.24 1.19 0.1

Notes. We note, that for non-linear functions, such as the truncated power-law bias, the means of function parameters do not necessarily agree to the mean of the bias function. As a comparison, in Fig. 6, we also plotted the bias function corresponding to the means of the parameter values.

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