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

	[[alternative HTML version deleted]]

