Fit Curve
Fit Built-In Nonlinear Models to Your Data
The Fit Curve platform enables you to fit models that are nonlinear in the parameters. In many situations, especially in the physical and biological sciences, well-known nonlinear equations describe the relationship between variables. For example, pharmacological bioassay experiments can demonstrate how the strength of the response to a drug changes as a function of drug concentration. Sigmoid curves often accurately model response strength as a function of drug concentration. Another example is exponential growth curves, which can model the size of a population over time.
The Fit Curve platform provides predefined models, such as polynomial, logistic, probit, Gompertz, exponential, peak, pharmacokinetic, rate, and dissolution models. The use of predefined models means that you are not required to create model formulas or specify starting values for parameter estimates. To specify your own starting values and create model formulas, use the Nonlinear platform, which can fit specified nonlinear models. See “Nonlinear Regression”.
Figure 14.1 Example of Nonlinear Fit in the Fit Curve Platform
