Bayesian approaches formulate the problem differently. Instead of saying the parameter simply has one (unknown) true value, a Bayesian method says the parameter's value is fixed but has been chosen …

Feb 17, 2021 · Confessions of a moderate Bayesian, part 4 Bayesian statistics by and for non-statisticians Read part 1: How to Get Started with Bayesian Statistics Read part 2: Frequentist …

Which is the best introductory textbook for Bayesian statistics? One book per answer, please.

Dec 3, 2020 · One of the continuous and occasionally contentious debates surrounding Bayesian statistics is the interpretation of probability. I am going to present both interpretations.

The Bayesian interpretation of probability as a measure of belief is unfalsifiable. Only if there exists a real-life mechanism by which we can sample values of $\theta$ can a probability distribution for …

@Xi'an's answer (below) helped me - clarifying that the Dirichlet distribution is A prior for the multinomial, not THE prior. It's chosen because it is a conjugate prior that works well to describe …

The Bayesian Choice for details.) In an interesting twist, some researchers outside the Bayesian perspective have been developing procedures called confidence distributions that are probability …

This is a very simple question but I can't find the derivation anywhere on the internet or in a book. I would like to see the derivation of how one Bayesian updates a multivariate normal distribut...

The concept is invoked in all sorts of places, and it is especially useful in Bayesian contexts because in those settings we have a prior distribution (our knowledge of the distribution of urns on the table) and …

The debate about non-informative priors has been going on for ages, at least since the end of the 19th century with criticism by Bertrand and de Morgan about the lack of invariance of Laplace's uniform …