We found that the N n 0 window method was the most robust truncation selection heuristic on these data. Its intermediate treatment of autocorrelation balanced the propensities for early and late truncation shown by methods ignoring correlation, and methods more completely accounting for correlation, respectively. Methods at the extremes of the correlation spectrum performed well on the early truncation point set and poorly on the late truncation point set or vice versa. In contrast, the N n 0 window method never performed more than 29 % worse (by RMSE) than the top-performing automated method. It also did not produce the wide and sometimes bimodal distributions of truncation times seen for the initial sequence estimators, which we view as an advantage in itself.