Learn what nonlinear regression models are, how they differ from linear regression models, and when they are suitable for data analysis.

Linear and nonlinear models are two types of mathematical functions that can be used to describe the relationships between variables. In this article, you will learn what they are, how they differ ...

We consider a nonlinear function-on-function additive regression model with multiple functional predictors. The forms of the nonlinear functions are unspecified, and offer great flexibility to model ...

Nonlinear mixed effects models (NLMMs) and self-modeling nonlinear regression (SEMOR) models are often used to fit repeated measures data. They use a common function shared by all subjects to model ...

Radial basis function-based state-dependent autoregressive (RBF-AR) models are a class of nonlinear combined models. This letter focuses on the parameter estimation for the RBF-AR models. To overcome ...

Literature on Nonlinear Mixed Models Davidian and Giltinan (1995) and Vonesh and Chinchilli (1997) provide good overviews as well as general theoretical developments and examples of nonlinear mixed ...

Author Dr. R. Russell Rhinehart discusses his new book, Nonlinear Model-Based Control: Using First-Principles Models in Process Control, and explains why nonlinear first-principles models should be ...

This paper provides a selective overview of nonlinear exchange rate models recently proposed in the literature and assesses their contribution to understanding exchange rate behavior. Two key ...