Bayesian methods use prior knowledge and beliefs to update the probability of a hypothesis based on new data. For example, if you want to estimate the proportion of people who prefer chocolate ...

In the sport of baseball, one of the most commonly cited statistics is the batting average, usually framed over an entire ...

If you’re a believer in Warren Buffett’s oft-cited quote — essentially to be greedy when others are fearful — you may want to ...

Researchers delved into the two “neutral” studies using Bayesian methods: a clearer picture of angiography’s role has emerged ...

Thirty-one members of the University of Chicago faculty have received distinguished service professorships or named ...

All of statistics and much of science depends on probability—an astonishing achievement, considering no one’s really sure ...

The goal: Given a set of independent samples (assignments of random variables), find the best (or the most likely) Bayesian Network (both DAG and CPDs). As shown in the figure below, we are given a ...

Abstract: To consider model uncertainty in global Fréchet regression and improve density response prediction, we propose a frequentist model averaging method. The weights are chosen by minimizing a ...

Book Abstract: Bayesian Bounds provides a collection of the important papers dealing with the theory and application of Bayesian bounds. The book is essential to both engineers and statisticians ...