>From the help document on KalmanLike, KalmanRun, etc.,
I see the linear Gaussian state space model is
a <- T a + R e
y = Z' a + eta
following the book of Durbin and Koopman.
In practice, it is useful to run Kalman
filtering/smoothing/forecasting with exogenous factor:
a <- T a + L b + R e
y = Z' a + M b + eta
where b is some known vector (a function of time).
Some other software like S-plus and Mathematica
include the above exogenous factor. SsfPack by
Koopman, etal. also has the factor built in the model
to accommodate practical uses.
So what is the rationale for R to leave off the
exogenous factor? Is there a feasible way to convert
the general model to the simple model in R?
Thanks,
Heng Sun
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