curve fitting toolbox documentation -凯发k8网页登录
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.
get started
learn the basics of curve fitting toolbox
linear and nonlinear regression
fit curves or surfaces with linear or nonlinear library models or custom models
interpolation
fit interpolating curves or surfaces, estimate values between known data points
smoothing
fit using smoothing splines and localized regression, smooth data with moving average and other filters
fit postprocessing
plotting, outliers, residuals, confidence intervals, validation data, integrals and derivatives, generate matlab® code
splines
construct splines with or without data; ppform, b-form, tensor-product, rational, and stform thin-plate splines