Discover how credibility theory helps actuaries use historical data to estimate risks and set insurance premiums; learn how ...

We discuss the problem of selecting among alternative parametric models within the Bayesian framework. For model selection problems, which involve non-nested models, the common objective choice of a ...

The FDA’s new draft guidance on Bayesian methodology signals a shift toward more flexible, data-driven clinical trial designs, enabling sponsors to use prior data and adaptive approaches to improve ...

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, ...