The need for a Bayesian wrapper
Via Frequentist inference only seems easy
Bayesian methods are not necessarily more painful that frequentist procedures. The Bayesian estimation procedure requires more from the user (the priors) and has an expensive and complicated convolution step to use the data to relate the priors to the posteriors (unless you are lucky enough to have something like the theory of conjugate distributions to hide this step). The frequentist estimation procedure seems to be as simple as “copy over your empirical observation as your estimate.