[R] Kalman Filter

[Spencer Graves]

      Have you looked at the 'dlm' package?  It has a vignette to help 
you learn to use it.  Also, I've heard that a book about that package is 
scheduled to appear in the next few months. 

      I have looked at the Kalman functions in the 'stats' package but 
have not found documentation that seemed sufficient to get me started 
using it. 

      RSiteSearch('Kalman', 'fun') produced 48 hits for me just now.  If 
you don't find what you want with 'dlm' (and maybe even if you do), you 
may wish to examine that list, if you haven't already. 

      Hope this helps. 
      Spencer

Vladimír Šamaj wrote:
> Hi
>
> My name is Vladimir Samaj. I am a student of Univerzity of Zilina. I am
> trying to implement Kalman Filter into my school work. I have some problems
> with understanding of R version of Kalman Filter in package stats( functions
> KalmanLike, KalmanRun, KalmanSmooth,KalmanForecast).
>
> 1) Can you tell me how are you seting the initial values of state vector in
> Kalman Filter? Are you using some method?
>
> 2) I have fond function StructTS in stats package. I dont understand, how
> exactly, are you computing(what method are you using) fitted values which
> are the output of this function( $fitted ) . In description od this function
> is that it fit a structural model for a time series by maximum likehood.
> Does it means, that the fitted values are fit by maximum likehood? If so how
> does look the likehood function?
>
> 3)Finaly, I dont understand smooting problem.  What I know is that, if I
> have t observations of some time serie, I can use  function KalmanRun to get
> estimates of state vector. And if I gain aditional observations of time
> serie( T > t ), I shoud use KalmanSmooth function to smooth estimates of
> state vector. I dont understand, that how shoud I "tell" to KalmanSmooth
> funtion that I allready did filtering and it shoud use the values from
> filtering to smoothing.
>
> I will be glad if you help me. I hope that my folmulations were correct.
>
> Thank you very much.
>
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>
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