Least Squares

Solve least-squares (curve-fitting) problems

Least squares problems have two types.

Linear least-squares solves min||C*x - d||², possibly with bounds or linear constraints. See Linear Least Squares.
Nonlinear least-squares solves min(∑||F(x_i) – y_i||²), where F(x_i) is a nonlinear function and y_i is data. See Nonlinear Least Squares (Curve Fitting).

Categories

Linear Least Squares
Solve linear least-squares problems with bounds or linear constraints
Nonlinear Least Squares (Curve Fitting)
Solve nonlinear least-squares (curve-fitting) problems in serial or parallel

Featured Examples

Nonlinear Data-Fitting

Nonlinear Data-Fitting

Basic example showing several ways to solve a data-fitting problem.

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Nonlinear Least-Squares, Problem-Based

Nonlinear Least-Squares, Problem-Based

Basic example of nonlinear least squares using the problem-based approach.

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Fit ODE Parameters Using Optimization Variables

Fit ODE Parameters Using Optimization Variables

Fit parameters of an ODE using problem-based least squares.

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