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Andrew,
Yes you can. First run the Kalman smoother to get an estimate of x_t. Then
your prediction, in fact, the conditional mean of y_{t+1},...,y_{t+10}
given the past is
y_{t+1} = CAx_t
y_{t+2} = CA^2 x_t
...
y_{t+10} = CA^{10} x_t
Hi @sbarratt !
How would i use the model to say predict 10 steps in the future.
Or does pykalman not have a prediction function.
Best,
Andrew
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