implementing kalman filter when Ht (the measurement matrix) is time varying

[tarikb02]

Hello,

I would like to implement kalman filter when the measurement matrix is time varying. the model is as follows:

Yt = Ht * Zt + Et    Ht = [ 1 Mt]                                                                                                                                                                                                           

Zt = Zt-1 + Vt.

can anyone tell how to do this with KALCVF in iml. My problem is that my Ht is time varying while in KALCVF I need Ht is time invariant.

Many thanks in advance.

tarik

[Rick_SAS]

A colleague sent me the following information regarding this question:

Actually the documentation does mention that a time-varying
measurement matrix, H_t, is permitted.  All you need to do is provide H_t
that is a ((T+lead)*N_y) times N_z matrix where, T is the number of time
points, lead is the forecast lead, N_y is the dimension of the observation
vector, and  N_z is the dimension of the state vector.   For
example, in the user’s notation, if the observations  are univariate, the
rows of H_t matrix will be [1 M_t], t=1 …(T +lead).

By the way, as a side note, mention to the user the new state
space modeling procedure, SSM, in 9.3 (its doc is at http://support.sas.com/documentation/cdl/en/etsug/63939/HTML/default/viewer.htm#etsug_ssm_sect006.ht...
).