  We perform an extrapolative analysis of "fast-growth" free-energy-difference
(DF) estimates of a computer-modeled, fully-solvated ethane<->methanol
transformation. The results suggest that extrapolation can greatly reduce the
systematic error in DF estimated from a small number of very fast switches. Our
extrapolation procedure uses block-averages of finite-data estimates, and
appears to be particularly useful for broad, non-Gaussian distributions of data
which produce substantial systematic errors with insufficient data. In every
tested case, the extrapolative results were better than direct estimates.
