Curve Fitting

Abstract

This chapter presents an overview of curve fitting methods in Euclidean spaces, with a particular emphasis on R 2 and R 3 . In order to represent linear and nonlinear interactions between numerous variables, a number of methodologies, including linear and nonlinear least squares methods, are being investigated. The linear relationship that exists between two variables is broken down in great detail, and a broad variety of examples are provided to show how curve fitting methods can be utilized to build models that are an accurate representation of data sets. In addition to this, the linear relationship that exists between the three variables under consideration is dissected, and detailed strategies for dealing with this scenario are discussed. Curve fitting methods are useful for exploring and evaluating data in Euclidean spaces, as shown by the results and examples shown below, which demonstrate the utility and versatility of these methods.

Keywords: R² space, R³ space, curve fitting, least squares method, linear least squares method, linear relationship between multiple variables, linear relationship between three variables, linear relationship between two variables, nonlinear least squares method, nonlinear relationship between multiple variables, nonlinear relationship between two variables.