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6 votes
Accepted

What is the Gold Standard for Evaluating the Posterior of a Bayesian Regression Model?

The method of choice to evaluate probabilistic predictions is a proper scoring rule. The Brier score is one such, for the special case of 0-1 outcomes - that is, classification. However, there are ...
Stephan Kolassa's user avatar
5 votes

How to fit a Bayesian model to a mixture of Beta and One-Zero inflated data?

Here is the best I could do I fit a zero-one inflated beta regression and allows the mean and the dispersion to be a smooth. The brms syntax is ...
Demetri Pananos's user avatar
3 votes

Example where the posterior from Jags and Stan are really different and have real impacts on decisions using the model

In a recent paper with Carlos Cinelli, "Causally sound priors for binary experiments," we demonstrate a simple 3-parameter model for which exact posterior sampling is possible and yet Stan ...
njirons's user avatar
  • 51
2 votes

What is the Gold Standard for Evaluating the Posterior of a Bayesian Regression Model?

There are multiple senses of "correct" you may want to invoke. A) - good predictions. If by "correct" you mean "has useful predictions", than cross validation (or better ...
Martin Modrák's user avatar
1 vote
Accepted

How to Derive the Conditional Variance in a Bivariate Normal Distribution After Bayesian Updating?

The posterior precision matrix of $(\theta_1,\theta_2)$ can be derived by adding the prior precision matrix and the precision matrix associated with the likelihood. However, the following alternative ...
Jarle Tufto's user avatar
  • 11.3k
1 vote

Understanding Empirical Bayes

To me it makes more sense to use Method of Moments (instead of MLE) to estimate the parameters α and β of the Beta prior. Ok, but that's not empirical Bayes. In classical Bayes, we have the ...
Guillaume Dehaene's user avatar
1 vote

How to fit a Bayesian model to a mixture of Beta and One-Zero inflated data?

TLDR: check that the method works on toy-data; check that the predicted conditional distributions at any $x$ are a good fit to the data. You already have several great technical answers. I want to try ...
Guillaume Dehaene's user avatar

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