Residual Analysis

Analyze residuals using whiteness and independence tests

Residuals are differences between the one-step-ahead predicted output from a model and the measured output from the validation data set. In other words, residuals represent the portion of the validation data not explained by the model.

Functions

`resid`	Compute and test residuals
`residOptions`	Option set for `resid`
`pe`	Prediction error for identified model
`peOptions`	Option set for `pe`
`fpe`	Akaike’s Final Prediction Error for estimated model
`aic`	Akaike’s Information Criterion for estimated model

Topics

What Is Residual Analysis?
Residuals are differences between the one-step-ahead predicted output from the model and the measured output from the validation data set.
How to Plot Residuals in the App
Create a residual analysis plot for linear and nonlinear models in the System Identification app.
How to Plot Residuals at the Command Line
Create a residual-analysis plot for linear and nonlinear models at the command line.
Examine Model Residuals
This example shows how you can use residual analysis to evaluate model quality.