Unfortunately, biological systems are often nonlinear and therefore need nonlinear models.

His research interests are in theoretical and applied statistics and nonlinear models of complex processes.

But in nonlinear models, their workings are not always easy to discern.

If a nonlinear model is fitted to the data one often needs to estimate coefficients through optimization.

Therefore more caution than usual is required in interpreting statistics derived from a nonlinear model.

General relativity is a highly nonlinear model, and as such, its 3+1D version is usually too complicated to analyze in detail.

The individual components are then assembled to create a full nonlinear model of the structure.

Similar it is possible to consider various nonlinear models of VCO.

One common difficulty in fitting nonlinear models is finding adequate starting values.

The estimated coefficients from this linear fit are used as the starting values for fitting the nonlinear model to the full data set.