One final note. Kalman filtering dramatically increases the time it takes to simulate a model . For large models, the execution of the Kalman filter also requires a large amount of memory. Basically memory requirements go up as the square of the number of Levels and computational requirements go up as the cube of the number of Levels. If you have a large model and need to run Kalman filtering you might want to see if you can create a smaller model that will do the filtering and use the resulting state estimates to drive the larger model.
