Curve Fitting Toolbox™ provides an app and functions for fitting curves and surfaces to data. The toolbox lets you perform exploratory data analysis, preprocess and post-process data, compare candidate models, and remove outliers. You can conduct regression analysis using the library of linear and nonlinear models provided or specify your own custom equations. The library provides optimized solver parameters and starting conditions to improve the quality of your fits. The toolbox also supports nonparametric modeling techniques, such as splines, interpolation, and smoothing.
After creating a fit, you can apply a variety of post-processing methods for plotting, interpolation, and extrapolation; estimating confidence intervals; and calculating integrals and derivatives.
Curve Fitting App
Fit curves using the Curve Fitting app or command-line fit functions.
Fit surfaces using the Curve Fitting app or command-line fit functions.
Apply linear regression by choosing from standard regression models or by using custom equations. All of the standard regression models include optimized solver parameters and starting conditions to improve fit quality.
Apply nonlinear parametric regression using exponentials, Fourier series, power series, Gaussians, and standard models.
Fit interpolating curves or surfaces, and estimate values between known data points.
Smooth data with moving average, smoothing splines, and localized regression.
Compare and Evaluate Fits
Create multiple fits, compare graphical and numerical results, and goodness-of-fit statistics. Use validation data to refine your fit.
Customize plotting and perform additional analyses such as outliers, residuals, confidence intervals, integrals, and derivatives.
Fitting Splines to Data
Fit various splines to data, including cubic and smoothing splines with various end conditions, for curves, surfaces, and higher dimensional objects.
B-Splines, Rational Splines, and NURBS
Create B-Splines and Uniform and Non-uniform Rational Splines (NURBS) for analysis of complex surfaces.