The real data are computationally expensive to generate and unsuitable for testing since the infinite-sampling results are unknown. Therefore, the initial transients and autocorrelation functions of the real data were estimated and used to generate large numbers of correlated synthetic time series from uncorrelated Gaussian noise. The properties of the synthetic time series did not need to exactly match the real data they were modelled on, only to be reasonably representative of absolute binding free energy data. Because the infinite sampling time results were known for the synthetic time series, truncation point selection heuristics could be evaluated by their RMSE to the infinite sampling time results.