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Basic example of nonlinear least squares using the problem-based approach. Nonlinear Data-Fitting Using Several Problem-Based Approaches. Solve a least-squares fitting problem using different solvers and different approaches to linear parameters. Fit ODE Parameters Using Optimization Variables.
- Nonlinear Data-Fitting
This example shows how to fit a nonlinear function to data...
- Lsqcurvefit
example. x = lsqcurvefit (fun,x0,xdata,ydata,lb,ub) defines...
- Least-Squares Fitting
Curve Fitting Toolbox supports the use of weights and robust...
- Nonlinear Curve Fitting with lsqcurvefit
lsqcurvefit enables you to fit parameterized nonlinear...
- Nonlinear Data-Fitting
This example shows how to fit a nonlinear function to data using several Optimization Toolbox™ algorithms.
example. x = lsqcurvefit (fun,x0,xdata,ydata,lb,ub) defines a set of lower and upper bounds on the design variables in x, so that the solution is always in the range lb ≤ x ≤ ub. You can fix the solution component x (i) by specifying lb (i) = ub (i). Note.
Curve Fitting Toolbox supports the use of weights and robust fitting to calculate the SSE for nonlinear models. The accuracy of a nonlinear model's predictions depends on the type of the model, the convergence criteria, the data set, and the initial values assigned to the coefficients.
If you are unfamiliar with nonlinear regression it is recommend that you read Fitting Curves to Data using Nonlinear Regression. This provides an overview of how nonlinear regression works and how to analyze the results. MATLAB can be used to t an arbitrary model equation to a set of data points. The MATLAB function that accomplishes this is nlin t
lsqcurvefit solves nonlinear data-fitting problems. lsqcurvefit requires a user-defined function to compute the vector-valued function F (x, xdata). The size of the vector returned by the user-defined function must be the same as the size of ydata.
lsqcurvefit enables you to fit parameterized nonlinear functions to data easily. You can also use lsqnonlin; lsqcurvefit is simply a convenient way to call lsqnonlin for curve fitting. In this example, the vector xdata represents 100 data points, and the vector ydata represents the associated measurements. Generate the data for the problem.
