Predict or Simulate Responses Using a Nonlinear Model This example shows how to use the methods predict, feval, and random to predict and simulate responses to new data.

This MATLAB function returns a vector of estimated coefficients for the nonlinear regression of the responses in Y on the predictors in X using the model specified by modelfun.

Learn about MATLAB support for nonlinear regression. Resources include examples, documentation, and code describing different nonlinear models.

In a nonlinear regression model, the response variable does not need to be expressed as a linear combination of model coefficients and predictor variables. You can perform a nonlinear …

This MATLAB function fits the model specified by modelfun to variables in the table or dataset array tbl, and returns the nonlinear model mdl.

Learn about MATLAB support for nonlinear model. Resources include code examples, videos, and documentation describing different nonlinear models.

Use the properties of a NonLinearModel object to investigate a fitted nonlinear regression model. The object properties include information about coefficient estimates, summary statistics, …

You can use linear and nonlinear regression to predict, forecast, and estimate values between observed data points. Curve Fitting Toolbox™ functions allow you to perform regression by …

This example shows how to fit a nonlinear regression model for data with nonconstant error variance.

This example shows how to do a typical nonlinear regression workflow: import data, fit a nonlinear regression, test its quality, modify it to improve the quality, and make predictions based on the …