Perhaps it is sufficient to add a category information for the parameters. So that I can be more flexible to assign parameters to a special function
Categories
Information about whether the parameter should be varied: free, fixed
Information about the type of parameter error_model, deterministic
Parse model structure from model parameters and error parameters
Stategy
prior parser already exists. This can be seen as a starting point.
For Binomial error, priors need to contain an additional information, e.g. Binomial(n=nzfe). No default values. All other transformations have to be done in sim.initialize.
Think about hierarchical structure
Parameter specification (priors)
Perhaps it is sufficient to add a category information for the parameters. So that I can be more flexible to assign parameters to a special function
Categories
Parse model structure from model parameters and error parameters
Stategy
prior parser already exists. This can be seen as a starting point. For Binomial error, priors need to contain an additional information, e.g. Binomial(n=nzfe). No default values. All other transformations have to be done in sim.initialize. Think about hierarchical structure
💡 this can also be done with characters
something along those lines could work.