Curve Fitting – General - Statistical Software

NCSS Statistical Software 351-1 NCSS, LLC. All Rights Reserved. Chapter 351 Curve Fitting General Introduction Curve Fitting refers to finding an appropriate mathematical model that expresses the relationship between a dependent variable Y and a single independent variable X and estimating the values of its parameters using nonlinear regression . An introduction to Curve Fitting and nonlinear regression can be found in the chapter entitled Curve Fitting , so these details will not be repeated here. Here are some examples of the Curve Fitting that can be accomplished with this procedure. This program is General purpose Curve Fitting procedure providing many new technologies that have not been easily available. It is preprogrammed to fit over forty common mathematical models including growth models like linear-growth and Michaelis-Menten.

These models provide a variety of curve shapes. Several of the models were developed for quite different physical processes but yield similar results. We now present examples and details of several of the preset models available. 1. Linear: Y=A+BX This common model is usually fit using standard linear regression techniques.

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