Comments (1)
Dear vickysun5,
at the present, SIPPY does not implement a function to perform k-step ahead prediction.
Your issue is very interesting and we may consider to include this possibility in a future release.
In the identification routine, the prediction error is now calculated as the difference between the actual output and its one-step ahead prediction, e.g., all the the previous outputs, depending on the model order, are used to build the current output.
Hoping to have answered your questions.
Do not hesitate to contact us for any additional doubts.
Best
from sippy.
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
- ARMA(X) Model prediction is a bit ambigious HOT 2
- 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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from sippy.