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 for curve and surface fitting
Linear and nonlinear regression with custom equations
Library of regression models with optimized starting points and solver parameters
Interpolation methods, including B-splines, thin plate splines, and tensor-product splines
Smoothing techniques, including smoothing splines, localized regression, Savitzky-Golay filters, and moving averages
Preprocessing routines, including outlier removal and sectioning, scaling, and weighting data
Post-processing routines, including interpolation, extrapolation, confidence intervals, integrals and derivatives