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?