How to create a list of random variables instead of using size parameter?

I’m specifying some parameters for fourier terms in my regression as follows:

    #Seasonality terms
    β_ssn = pm.Laplace('β_ssn', mu = 0, b = 0.04, shape = (cat_len, 2*fourier_dim))

What I want to do, though, is have a separate b parameter for each prior. I want to have more regularizing priors for the higher dimensional terms. How would I go about doing this?

The best way to do this is passing a np.ndarray to b, it will parameterized it to have separate prior.


Awesome this worked!!