System Identification Toolbox | ![]() ![]() |
Compute loss functions for a set of different model structures of single-output ARX type.
Syntax
Description
NN
is a matrix that defines a number of different structures of the ARX type. Each row of NN
is of the form
with the same interpretation as described for arx
. See struc
for easy generation of typical NN
matrices for single-input systems.
Each of ze
and zv
are iddata
objects containing output-input data. Models for each of the model structures defined by NN
are estimated using the data set ze
. The loss functions (normalized sum of squared prediction errors) are then computed for these models when applied to the validation data set zv
. The data sets, ze
and zv
, need not be of equal size. They could, however, be the same sets, in which case the computation is faster.
Note that arxstruc
is intended for single-output systems only.
The output argument V
is best analyzed using selstruc.
It contains the loss functions in its first row. The remaining rows of V
contain the transpose of NN
, so that the orders and delays are given just below the corresponding loss functions. The last column of V
contains the number of data points in ze
. The selection of a suitable model structure based on the information in v
is normally done using selstruc
. See Model Structure Selection and Validation in the "Tutorial" for advice on model structure selection and cross-validation.
See Algorithm Properties
for an explanation of maxsize
.
Examples
Compare first to fifth order models with one delay using cross-validation on the second half of the data set. Then select the order that gives the best fit to the validation data set.
See Also
arx
, ivstruc
, n4sid
, selstruc
, struc
![]() | arxdata | bj | ![]() |