I have described my model in :

I find that it has some identification problem and I may get the local maxima when I set a very tiny prior for all parameters.

I have two questions:

- how can I search the parameters which cause the identification problems. And how can I solve this identification problem
- If using kalman filter. I find that researchers usually the procedure of repeatedly generating a random vector of starting values, and maximize the log-likelihood function, by using Nelder-Mead maximization algorithm and choosing 100 largest resulting values. So can stan have some functions to avoid the local maxima?

Some suggestions?

Very thank~