User`s guide

8 Model Analysis
Data for Validating Models
For plots that compare model response to measured response, such as model
output and residual analysis plots, you designate two types of data sets: one
for estimating the models (estimation data), and the other for validating the
models (validation data). Although you can designate the same data set to be
used for estimating and validating the m odel, you risk over fitting your data.
When you validate a model using an independent data set, this process is
called cross-validation.
Note Validation data should be the same in frequency content as the
estimation data. If you detrended the estimation data, you must remove the
same trend from the validation data. For more information about detrending,
see “Subtracting Trends from Signals (Detrending)” on page 1-94.
Supported Model Plots
The following table summarizes the types o f supported model plots.
Plot Type Suppor ted Models
Learn More
Model Output All linear and nonlinear
models
“Using Model Output
PlotstoValidateand
Compare Models” on
page 8-8
Residual Analysis All linear and nonlinear
models
“Using R esidual
Analysis Plots to
Validate Models” o n
page 8-16
Transient R esponse
• All linear p arametric
models
• Correlation analysis
(nonparametric)
models
• For nonlinear
models, only step
response.
“Using Impulse- and
Step-Response Plots to
Validate Models” o n
page 8-24
8-4