  In this article, it is described how to use statistical data analysis to
obtain models directly from data. The focus is put on finding nonlinearities
within a generalized additive model. These models are found by the means of
backfitting algorithms or more general versions, like the alternating
conditional expectation value method. The method is illustrated by numerically
generated data. As an application the example of vortex ripple dynamics, a
highly complex fluid-granular system is treated.
