Hello,
thanks for answer my Question. I prefer use KalmanLike(y, mod, nit = 0,
fast=TRUE). For parameter estimating I have a given time series. In these
are several components: Season and noise; furthermore it gives a mean
reversion process. The season is modelled as a fourierpolynom. From the
given time series I have to estimate the
- Season parameters
- The mean reversion factor
- variance from the noise
I think in the function KalmanLike y is the vector of the time series; what
does "mod" mean? How can I write the syntax for the state space?
Have anybody a simple example for better understanding KalmanLike. Or is it
better to use other packages for parameter estimating?
I have no experience in work with Kalman filters and I'm a new R user.
Thanks for helping.
Best,
Thomas
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