Skip to main content
ARS Home » Research » Publications at this Location » Publication #59206
Title: ANALYZING DATA WITH NONLINEAR REGRESSION - CHAPTER 2

Author
item RUSLING, JAMES - UNIV. OF CONNECTICUT
item Kumosinski, Thomas

Submitted to: Nonlinear Computer Modeling of Chemical and Biochemical Data
Publication Type: Book / Chapter
Publication Acceptance Date: 5/4/1995
Publication Date: N/A
Citation: N/A

Interpretive Summary: BOOK CHAPTER, interpretive summary is not required.

Technical Abstract: Chapter 2 is concerned with how data are analyzed with nonlinear regression methods. It compares nonlinear and linear models for analyzing laboratory data. A tutorial of the linear model is presented, as are the equations of linear regression analysis. Matrix representation of the linear least squares method is derived. Why the error increases when models are linearized, is also discussed. Next the nonlinear regression model is presented, along with the nonlinear regression algorithms. The matrix representation of the nonlinear regression is derived in total. An example of regression analysis for an exponential decay with and without weighting functions is discussed. Finally, sources of software for regression analysis are provided and contrasted.