  We describe an R package developed by the research group Turbulence, Wind
energy and Stochastics (TWiSt) at the Carl von Ossietzky University of
Oldenburg, which extracts the (stochastic) evolution equation underlying a set
of data or measurements. The method can be directly applied to data sets with
one or two stochastic variables. Examples for the one-dimensional and
two-dimensional cases are provided. This framework is valid under a small set
of conditions which are explicitly presented and which imply simple preliminary
test procedures to the data. For Markovian processes involving Gaussian white
noise, a stochastic differential equation is derived straightforwardly from the
time series and captures the full dynamical properties of the underlying
process. Still, even in the case such conditions are not fulfilled, there are
alternative versions of this method which we discuss briefly and provide the
user with the necessary bibliography.
