# data points, from Andreon (2012)
#lgM500    lgMstar500  lgMstar200
#     err        err         err
14.78 0.04 12.66 0.05  12.80 0.05 
14.09 0.06 12.46 0.12  12.64 0.09 
14.90 0.04 12.59 0.08  12.70 0.08 
13.89 0.05 12.25 0.14  12.40 0.13 
13.59 0.03 11.97 0.14  12.00 0.14 
13.69 0.05 12.08 0.20  12.12 0.25 
13.90 0.06 12.33 0.12  12.48 0.10 
13.30 0.07 12.11 0.15  12.29 0.12 
13.72 0.06 12.05 0.15  12.10 0.16 
13.90 0.07 12.43 0.16  12.51 0.11 
13.95 0.08 12.34 0.10  12.44 0.08 
13.93 0.09 12.39 0.12  12.58 0.11 


# fit results, from Andreon (2012)
# fit lgMstar500-lgM500
# mm is the mean model (blue line)
# ll is the mean model - 1 sigma (lower end of 68% interval)
# uu is the mean model + 1 sigma (upper end of 68% interval)
#lgM500 ll    mm    uu
13.2 11.94 12.02 12.10 
13.3 11.98 12.06 12.12 
13.4 12.04 12.10 12.17 
13.5 12.08 12.14 12.20 
13.6 12.13 12.18 12.24 
13.7 12.17 12.21 12.27 
13.8 12.21 12.25 12.30 
13.9 12.25 12.29 12.33 
14.0 12.29 12.33 12.37 
14.1 12.33 12.37 12.40 
14.2 12.37 12.41 12.44 
14.3 12.41 12.44 12.48 
14.4 12.45 12.48 12.52 
14.5 12.49 12.52 12.56 
14.6 12.52 12.56 12.60 
14.7 12.56 12.60 12.64 
14.8 12.59 12.64 12.69 
14.9 12.63 12.67 12.73 
15.0 12.66 12.71 12.77 
15.1 12.69 12.75 12.82 
15.2 12.73 12.79 12.86 


# fit results, from Andreon (2012)
# fit lgMstar200-lgM500  note different radius for ascissa and ordinate 
# mm is the mean model (blue line)
# ll is the mean model - 1 sigma (lower end of 68% interval)
# uu is the mean model + 1 sigma (upper end of 68% interval)
#M500 ll    mm    uu
13.2 12.09 12.17 12.24 
13.3 12.14 12.21 12.28 
13.4 12.18 12.24 12.31 
13.5 12.21 12.28 12.33 
13.6 12.27 12.32 12.37 
13.7 12.30 12.36 12.40 
13.8 12.35 12.39 12.44 
13.9 12.39 12.43 12.47 
14.0 12.43 12.47 12.51 
14.1 12.48 12.51 12.54 
14.2 12.52 12.54 12.59 
14.3 12.55 12.58 12.62 
14.4 12.59 12.62 12.66 
14.5 12.62 12.66 12.70 
14.6 12.65 12.69 12.74 
14.7 12.68 12.73 12.78 
14.8 12.72 12.77 12.83 
14.9 12.75 12.81 12.87 
15.0 12.77 12.85 12.91 
15.1 12.81 12.88 12.96 
15.2 12.84 12.92 13.00