Ngroup = 5 Ntrials = 10000 Pflyer = 0 %%%%%%%%%% Normally distributed points sigma_flyer = 5 size_ratio = 1.5000 time_elapsed_sec = 91.997 O = What is the fractional uncertainty in each width measure? = O rmsrad1_err = 0.25605 extspr1_err = 0.27139 lextspr1_err = 0.30263 O = How often does each method rank groups r1 & r2 correctly? = O rmsrad_success = 0.86310 extspr_success = 0.84840 lextspr_success = 0.82610 %%% All three methods work about equally well with normally distributed data! Ngroup = 5 Ntrials = 10000 Pflyer = 0.10000 %%%%%%%%%% 10% outliers ("flyers") sigma_flyer = 5 size_ratio = 1.5000 time_elapsed_sec = 91.786 O = What is the fractional uncertainty in each width measure? = O rmsrad1_err = 0.64100 extspr1_err = 0.67413 lextspr1_err = 0.52962 O = How often does each method rank groups r1 & r2 correctly? = O rmsrad_success = 0.71200 extspr_success = 0.70320 lextspr_success = 0.77680 %%% Outliers degrade the performance of all 3 methods significantly. %%% Less-extreme-spread gains a significant advantage when there are outliers. Ngroup = 5 Ntrials = 10000 Pflyer = 0.20000 %%%%%%%%%% 20% outliers ("flyers") sigma_flyer = 5 size_ratio = 1.5000 time_elapsed_sec = 92.225 O = What is the fractional uncertainty in each width measure? = O rmsrad1_err = 0.59779 extspr1_err = 0.62606 lextspr1_err = 0.63722 O = How often does each method rank groups r1 & r2 correctly? = O rmsrad_success = 0.67810 extspr_success = 0.67440 lextspr_success = 0.71730