I recently started to use PyMC3, and have a question.
Is it possible to use PyMC3 to fit data in which each sample (this could be a discrete time sample, for example) has measurements of several different quantities associated with it, all of which are predicted by a different function of the parameters of an underlying model). That is, each sample is described by a vector, rather than a scalar.
If this is possible, how would I need to modify a statement such as
Y_obs = Normal(‘Y_obs’, mu=mu, sd=sigma, observed=Y)