
That is because the Kalman filter is only an estimation method. You will have to specify the 
matrices A and C in:

y_t = A_t * x_t + noise_t

x_t = C *x_t-1 + noise_t


where you plug the explanatory variables in A_t. The Kalman filter will then give you estimates 
of the state vector x_t...which includes your time varying coefficients. You will also need to 
add an optimisation routine on top of the Kalman filter to estimate any unknown parameters.

Not difficult...requires a bit of programming.

Alain 

---------------------
Dr Alain Zuur
Highland Statistics Ltd.
www.highstat.com
www.brodgar.com



Message: 3 
Date: Wed, 7 Apr 2004 11:52:36 +0100 
From: Arnaud_Amsellem@ssga.com 
Subject: [R] Time Varying Coefficients 
To: r-help@stat.math.ethz.ch 
Message-ID: 
<OF82C114A6.D20745CD-ON80256E6F.003B34AF-80256E6F.003BBFCE@statestr.com> 

Content-Type: text/plain; charset=us-ascii 

I'd like to estimate time varying coefficients in a linear regression using 
a Kalman filter. 
Even if the Kalman Filter seems to be available in some packages I can't 
figure out how to use it to estimate the coefficients. 
Is there anyway to do that in R? 

Any help appreciated 

Thanks


