I am learning Bayesian statistics. I found that this pymc3 introduction sometimes uses MAP to estimate the parameters for the MCMC input (the regression example), but the intro doesn't run MAP for Stochastic Vol and Coal Disaster cases.
I understand that when the mode is not representative or if we have experts specifying explicitly the prior we shouldn't use MAP.
Assuming that we know nothing much about the data, and just draft the hierarchical model and we have no help from experts, should we always run MAP to find out the initial point estimates before doing MCMC? e.g. The stochastic vol and coal disaster examples should we also run MAP?