# Fit Postprocessing

Plotting, outliers, residuals, confidence intervals, validation data, integrals and derivatives, generate MATLAB® code

After fitting a curve or surface, use postprocessing methods to analyze if the fit to the data is accurate. After creating a fit, you can apply various postprocessing methods for plotting, interpolation, and extrapolation; estimating confidence intervals; and calculating integrals and derivatives. You can also use postprocessing methods to determine the outliers of a fit.

You can use Curve Fitting Toolbox™ functions to evaluate a fit by plotting the residuals and the prediction bounds. For more information, see Evaluate Curve Fit. To compare fits and generate MATLAB code interactively, use the Curve Fitter app.

## Apps

 Curve Fitter Fit curves and surfaces to data

## Functions

 `cfit` Constructor for `cfit` object `coeffnames` Coefficient names of `cfit`, `sfit`, or `fittype` object `coeffvalues` Coefficient values of `cfit` or `sfit` object `confint` Confidence intervals for fit coefficients of `cfit` or `sfit` object `differentiate` Differentiate `cfit` or `sfit` object `feval` Evaluate `cfit`, `sfit`, or `fittype` object `integrate` Integrate `cfit` object `plot` Plot `cfit` or `sfit` object `predint` Prediction intervals for `cfit` or `sfit` object `probvalues` Problem-dependent parameter values of `cfit` or `sfit` object `quad2d` Numerically integrate `sfit` object `sfit` Constructor for `sfit` object

## Topics

• Create Multiple Fits in Curve Fitter App

Workflow for refining your fit, comparing multiple fits, and using statistics to determine the best fit.

• Explore and Customize Plots

In the Curve Fitter app, display fit, residual, surface, or contour plots; display prediction bounds and multiple plots; use zoom, pan, data cursor, and outliers modes; change colormap of surface and contour plots, change axes limits and print plots.

• Export Fit from Curve Fitter App to Simulink Lookup Table

Export a surface fit from the Curve Fitter app to a Simulink® 2-D lookup table.

• Remove Outliers

Remove points interactively or exclude them by rule in the Curve Fitter app. Alternatively, exclude outliers by using the `fit` function. You can exclude data based on their distance from the model, in standard deviations.

• Select Validation Data

Compare your fit with validation data or test set in the Curve Fitter app.

• Generate Code and Export Fits to the Workspace

Generate MATLAB code from an interactive session in the Curve Fitter app, recreate fits and plots, and analyze fits in the workspace.

• Evaluate Curve Fit

This example shows how to work with a curve fit.

• Evaluate Surface Fit

This example shows how to work with a surface fit.

• Evaluating Goodness of Fit

After fitting data with one or more models, evaluate the goodness of fit using plots, statistics, residuals, and confidence and prediction bounds.

• Compare Fits in Curve Fitter App

Find the best fit by comparing visual and numeric results, including fitted coefficients and goodness-of-fit statistics.

• Compare Fits Programmatically

This example shows how to fit and compare polynomials up to sixth degree using Curve Fitting Toolbox™, fitting some census data.

• Residual Analysis

The residuals from a fitted model are defined as the differences between the response data and the fit to the response data at each predictor value.

• Confidence and Prediction Bounds

Curve Fitting Toolbox software lets you calculate confidence bounds for the fitted coefficients, and prediction bounds for new observations or for the fitted function.

• Differentiating and Integrating a Fit

This example shows how to find the first and second derivatives of a fit, and the integral of the fit, at the predictor values.