Specify different prior distribution only for some variables in the variables dim

Questions v5
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3

I think that my formulation of the problem without code is very inaccurate :slight_smile:
Here i define some coords where I will set mutltiple priors for “delay_vars”. There will be priors on some non-linear transformations as well as on model coefficients. It would be very inefficient to specify som 15 priors (3 for each variable). Only priors for “alpha” parameter would be different between the “delay_vars”. So far, I can set priors which are common for all variables in “delay_vars” but I would like to change just some of them.

delay_vars = ['tv_S', 'ooh_S', 'print_S', 'facebook_I', 'search_clicks_P', 'newsletter']
…

coords = {
    'date': df_scaled[date_var].values,
    'delay_vars': delay_vars,
    'control_vars': control_vars,
}

…

with pm.Model(coords=coords) as custom_model:
    beta_delay_vars = pm.HalfNormal(
        name='beta_delay_vars',
        sigma=1,
        dims='delay_vars'
    )  # the same for all delay_vars

    alpha = pm.Beta(name='alpha', alpha=1, beta=3,
                    dims='delay_vars')  # to be defined for some vars separately