[R] How to reconcile Kalman filter result (by package dlm) with linear regression?

  Hello All,   I am working with dlm for the purpose of estimating and forecasting with a Kalman filter model. I have succesfully set up the model and started generating results. Of course, I need to somehow be sure that the results make sense. Without any apparent target to compare with, my nat

[R] Package dlm generates unstable results?

  Hi, All,   This is the first time I seriously use this package. However, I am confused that the result is quite unstable. Maybe I wrote something wrong in the code? So could anybody give me some hint? Many thanks.   My test model is really simple. Y_t = X_t * a_t + noise(V)，(no Intercept h

[R] Seeking advice on dynamic linear models with matrix state variable.

  Hello, fellow R users,   I recently need to estimate a dynamic linear model in the following form:   For the measurement equation:   Y_t = F_t * a_t + v_t   where Y_t is the observation. It is a 1 by q row vector for each t. F_t is my forecasting variable. It is a 1 by p row vector. a_t is my st

[R] Any help understand the FKF package? Thanks.

  Dear Fellow R Users, I am experimenting right now the FKF package. I started by working out the first example included in the package and I am already confused. Would you offer some kind suggestions? What I want to do is to write down the state transition equation and the measurement equation