Nonlinearity

Nonlinearity is a relationship which cannot be explained as a linear combination of its variable inputs. In other words, the outcome does not change in proportion to a change in any of the inputs.

Nonlinearity is a common issue when examining cause-effect relations. Such instances require complex modeling and hypothesis to offer explanations to nonlinear events. Nonlinearity without explanation can lead to random, unforecasted outcomes such as chaos.

Nonlinear regression is a common form of regression analysis used in the financial industry to model nonlinear data against independent variables in an attempt to explain their relationship. Although the model's parameters are nonlinear in nature, nonlinear regression can fit data using methods of successive approximations to offer explanatory outputs.