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Linear and Nonlinear Regression Analysis by Navid Mostoufi; Alkis Constantinides is a book available to read on EtoBox.

What is Linear and Nonlinear Regression Analysis about?

Regression analysis is the application of mathematical and statistical methods for the analysis of the experimental data, and the fitting of the mathematical models to these data by the estimation of the unknown parameters of the models. The series of statistical tests, which normally accompany regression analysis, serve in model identification, model verification, and efficient design of the experimental program. Most mathematical models encountered in engineering and science are nonlinear in the parameters. Attempts at linearizing these models, by rearranging the equations and regrouping the variables, were common practice in the pre-computer era when graph paper and the straightedge were the tools for fitting models to experimental data. Such primitive techniques have been replaced by the implementation of linear and nonlinear regression methods on the computer. In this chapter, after giving a brief review of statistical terminology, we develop the basic algorithm of linear regression and then show how this is extended to nonlinear regression. We develop the methods in matrix notation so that the algorithms are equally applicable to fitting single or multiple variables, and to u

Author

Navid Mostoufi; Alkis Constantinides

Publisher

Elsevier

Published

2023

Language

EN