Running the model with dynamic calibration the parameter values don’t seem to be very stable. For instance, plotting the parameter values from each population in each window, we can see that the values within window 1 (running the model for 14 days with dynamic calibration), are at times quite different to window 2 (running for 28 days with DC). Also within each window, the values for each population are quite different.
In the initial model calibration process the parameter values are also unstable. I ran this for 28 days, using 9 populations and it doesn’t really seem like even after that period that the parameter distributions are becoming stable from one population to the next
Running the model with dynamic calibration the parameter values don’t seem to be very stable. For instance, plotting the parameter values from each population in each window, we can see that the values within window 1 (running the model for 14 days with dynamic calibration), are at times quite different to window 2 (running for 28 days with DC). Also within each window, the values for each population are quite different.
In the initial model calibration process the parameter values are also unstable. I ran this for 28 days, using 9 populations and it doesn’t really seem like even after that period that the parameter distributions are becoming stable from one population to the next