This new edition represents the most up-to-date treatment of nonlinear regression topics and applications available using the academically-preferred R language throughout. It offers a balanced presentation of the theoretical, practical, and computational aspects of nonlinear regression and provides background material on linear regression, including the geometrical development for linear and nonlinear least squares. The authors employ real data sets throughout, and their use of geometric constructs and continuing examples (some in the form of extensive case studies) makes the progression of ideas appear very natural.