A Journey Through Bayesian Posterior Summarization
<p>This blog post delves into the core concepts of Bayesian statistics, including posterior distributions, point estimates, and loss functions. We’ll explore how to summarize posterior distributions using grid approximations, percentile intervals, and highest posterior density intervals (HPDIs), and discuss the importance of choosing the right loss function for making optimal decisions.</p>
<p>We are continuing our journey to discover the great book Statistical Rethinking by Richard McElreath.</p>
<p><a href="https://blog.stackademic.com/a-journey-through-bayesian-posterior-summarization-70183c5441aa"><strong>Learn More</strong></a></p>