2. Setting up calibration and priors outside the model file

Outside the model file, fixed parameters and priors are separated.

Fixed parameters can be given in a cell array:

params = {
    'rho',   0.6
    'beta',  0.998
    ...
    'kappa', 161
};

or as a structure:

params       = struct();
params.rho   = 0.6;
params.beta  = 0.998;
...
params.kappa = 161;

The parameterization is then pushed into the model object:

m = set(m, parameters = params);

Priors for Bayesian (and MLE) estimation are given as a structure; see Estimation for the five distinct parametrisations (uniform, mean+std, quantile, raw hyperparameters, user-defined PDF), the Dirichlet form for transition-matrix rows, and the full endogenous-priors facility.