NonlinearRegression`
NonlinearRegression`

NonlinearRegress

As of Version 7.0, NonlinearRegress has been superseded by NonlinearModelFit and is part of the built-in Wolfram Language kernel.

NonlinearRegress[data,expr,pars,vars]

finds numerical values of the parameters pars that make the model expr give a best fit to data as a function of vars and provides diagnostics for the fitting.

NonlinearRegress[data,{expr,cons},pars,vars]

finds a best fit and provides diagnostics subject to the constraints cons.

Details

Examples

open allclose all

Basic Examples  (1)

Nonlinear regression with parameters a and b:

Options  (5)

ConfidenceLevel  (1)

Nonlinear regression with 99% confidence intervals:

RegressionReport  (1)

Nonlinear regression with a specific list of report values:

Weights  (2)

Weighted regression with specific weights given for each data element:

Weighted regression with weights equal to the squares of the measured responses:

WorkingPrecision  (1)

Nonlinear regression using precision 20: