I’m somewhat new to bayesian statistics, but am loving brms - it’s brilliantly solving challenging variable selection and distributional regression problem I have. I have a question about the interpretation of the Est.Error column when using extended families - in my case I’m using a zero-one inflated beta distribution. What I’m curious about is what factors effect the choice of summary statistic when interested in the “width” and flatness of the posterior, in particular with the zero-one inflated beta distribution. My use case involves predicting hundreds of thousands of out-of-sample values, so inspecting the posteriors of individual predictions isn’t feasible
In addition, I’m interested in comparing the accuracy of different summary statistics of central tendency of the posterior against point-estimates obtained from some frequentist models, but I’m stalled on how to pull the appropriate parameters out of the fitted brms model object.
Can anyone recommend a primer on summary stats for zero-one inflated beta?