How to create hierarchical prior for Bayesian estimation

Hi All,
I am wondering that how can I create hierarchical prior for Bayesian estimation in Dynare?
Thank you.
Kind regards,
Jesse

Please provide more details what you would like to do.

Dear Johannes,
Thank you very much replying.
I am applying a mixture normal to one of the shocks in my DSGE model, and the mixture normal distribution requires a weighted average of a number of normal distributions, for Bayesian estimations, I need to sample sample the hyperparameter- the weights first, before I can sample shocks from the mixture normal distribution for my shock.
I have prepared a distribution for weights already, but I need to sample weights first, then i used the weights obtained from my sampling to formulate the mixture normal distribution (the parameters contain weights), then I can sample my shock from the mixture distribution.
Kind regards,
Jesse

Why do you need to sample shocks for the estimation? Are you doing particle filtering?

Dear Johannes,
Thank you for your reply and sorry to reply you late. No, I am using Kalman filter, however, one of my shocks follows a Gaussian Mixture distribution-a weighted average of normal distributions with different means and variances. I need to sample weight paramters, mean parameters, variances parameters first, then once i get these prior parameters, i can sample shocks from the Gaussian mixture distributions.
Kind regards,
Jesse

Sorry, but I still don’t get it. Where during Kalman filtering do you need to sample shocks?