  Large sampling intervals can affect reconstruction of Kramers-Moyal
coefficients from data. A new method, which is direct, non-stochastic and exact
up to numerical accuracy, can estimate these finite-time effects. For the first
time, exact finite-time effects are described analytically for special cases;
biologically inspired numerical examples are also worked through numerically.
The approach developed here will permit better evaluation of Langevin or
Fokker-Planck based models from data with large sampling intervals. It can also
be used to predict the sampling intervals for which finite-time effects become
significant.
