Comments (2)
Dear Ferus-TUB,
thank your useful comment.
You are right, the notation about validation function in the user guide was indeed (very) ambiguous, if not confusing!
We fixed it and uploaded a new version of the guide on the repo.
Please note that the validation function is actually for prediction scopes (1- or k-step ahead).
If you want to simulate your identified model with only the input, you can use the standard lsim function of control.matlab package.
Best regards
SIPPY team
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Dear Sippy Team,
I'm still confused at this point.
My understanding of a system identification is that you have 3 basic steps:
- System identification by using input-output data + model structure
- Verification/Validation using new input output Data to confirm your system
- Prediction of the output using input and past predicted outputs
If I follow these basic steps I can see in your documentation that the method system_identification(y, u, 'ARMAX')
mets obviously the first step.
Now it gets kinda confusing. The method fset.validation
seems to be for validating the system by using new input output data and thus fullfills the second step. This seems to be in line with regards to your documentation where it says:
"This function is very useful when the user wants to cross-validate the identified input/output model, that is, test the previously identified model on new data not used in the identification stage"
But in your previous comment you mentioned that this method is intended for prediction scope. So my understanding in that case would be that it is intended for step 3.
Can you further clarrify on this matter?
If the method fset.validation
would be used for validation and also for prediction then I would suggest to change up the code and/or the documentaion because the equation 7.1 is then still ambigious, because in the case of prediction wouldn't the system just pass through the y_k and ignore everything else. Because y_k would be the best estimate for yhat_k.
Edit: Didn't mean to close it.
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Related Issues (20)
- Please update document SS_max_order or SS_orders if a valid IC is used. HOT 1
- Why the SS_threshold is 0.0 HOT 3
- Fails to install under Windows HOT 4
- Output of the identified model Yid is not correct HOT 6
- io_opt - bad import? HOT 1
- NameError: name 'Nb' is not defined HOT 6
- Support new Pythons HOT 7
- Invalid license?
- BJ identification
- Box-Jenkins MIMO- Invalid Transfer functions HOT 1
- Setup script exited with Problem with the CMake installation HOT 3
- SIMO/SISO model verification with functionset.validation HOT 4
- How to install it through Anaconda? HOT 1
- Some suggestions
- Forecasting with trained model
- Problem with model simulation
- a bug in the example codes? HOT 5
- Problem for simulating Linear Parameter Varying Model
- Regarding prediction and identified coefficient of input/output models. HOT 8
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