For the relatively low variance and correlation T4L system, all methods consistently selected discard times very close to 0 ns, producing RMSEs within uncertainty of the optimal fixed truncation time limit (at 0 ns -Section S4). It was reassuring to observe this expected behaviour. However, for the relatively high variance and correlation PDE2a system, methods which more fully accounted for autocorrelation were increasingly prone to over-discarding data (Figure ). This was particularly true for the initial sequence methods, which occasionally discarded over half of the data despite the lack of any bias. This was reflected by increases in the RMSEs. The "Initial Sequence: Positive" method should produce the largest variance of the mean estimates for a given time series because it chooses the latest truncation point for the autocovariance series and does not reduce the autocovariance sum by enforcing monotonicity or convexity of the gamma series. This method was the most prone to over-discarding data, corroborating the trend that generalised MSER methods which produce larger variance of the mean estimates are more prone to erroneously discarding data.