General data characteristics:
-----------------------------
This is a time domain data set with 1 input(s) and 1 output(s), 2001 samples
and 1 experiment(s).
All inputs in the data have been denoted as 'zero order hold' ('zoh'), i.e.
they are assumed to be piecewise constant over the sample time.
If the input is a sampled continuous signal and you plan to build or convert to
continuous-time models, it is recommended to mark the InterSample property as
'First order hold': Data.InterSample = 'foh' or Data.InterSample =
{'foh','foh', ...} for multi-input signals.
Some inputs and/or outputs have non-zero means. It is generally recommended to
remove the means by DAT = DETREND(DAT), except in the following cases:
1. The signals are measured relative to a level that corresponds to a physical
equilibrium. This could e.g. be the case if step responses are recorded from an
equilibrium point. In this case, it is advisable to remove the equilibrium
values rather than data means. You may do so using a TrendInfo object with
DETREND command, or during estimation using the "InputOffset" and
"OutputOffset" estimation options.
2. There is an integrator in the system, and the input and output levels are
essential to describe the effect of the integration.
3. You are going to use the data to estimate nonlinear ARX models.
Excitation level in data:
-------------------------
The input is persistently exciting of order 2. This means that you will
encounter problems if estimating models of order higher than 2.
Possibility of feedback in data:
--------------------------------
There is no significant indication of feedback in the data.
Use the "checkFeedback" command for assessment of feedback with more options.
Possibility of nonlinearity:
----------------------------
There is an indication of nonlinearity in the data.
A nonlinear ARX model of order [4 4 1] and idTreePartition function performs
better prediction of output than the corresponding ARX model of the same order.
Consider using nonlinear models, such as IDNLARX, or IDNLHW. You may also use
the "isnlarx" command to test for nonlinearity with more options.
