So, based on your reply, I imagine the easy solution you meant is to set something like this up in PyMC3,
\texttt{with pm.Model() as model:} \\ \ \ \ \ \ \ \ \ f(x_i) = series1_i + series2_i + series3_i + \ldots \ \ \ \text{*some regular regression*}\\ \ \ \ \ \ \ \ \ \texttt{sd_prior = pm.HalfNormal('sd_prior', sd = 3)} \\ \ \ \ \ \ \ \ \ \texttt{observed = pm.Normal('observed', mu = }f(x_i)\texttt{, sd = sd_prior,} \\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \texttt{observed = ???)} \\ \ \ \ \ \ \ \ \ \texttt{trace = pm.sample()}
Which helped me conceptually, but how would I set this up in PyMC3? I am not sure how to set up this regression, and what would I set equal to observed in pm.Normal() then?
Would you give me a quick example?