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: [EMAIL PROTECTED] Subject: [R] Time Varying Coefficients To: [EMAIL PROTECTED] Message-ID: <[EMAIL PROTECTED]> 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 ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
