We present a Bayesian hierarchical model for detecting differentially expressing genes that includes simultaneous estimation of array effects, and show how to use the output for choosing lists of ...

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, ...

This paper extends the Bayesian Model Averaging framework to panel data models where the lagged dependent variable as well as endogenous variables appear as regressors. We propose a Limited ...

Discover how credibility theory helps actuaries use historical data to estimate risks and set insurance premiums; learn how the Bayesian and Buhlmann methods relate.

Learn to apply Bayes' theorem in financial forecasting for insightful, updated predictions. Enhance decision-making with ...