BACKGROUND Much of our knowledge of the epidemiology and demography of HIV epidemics in Africa is derived from models fit to sparse, non-representative data. These often average over age and other ...

A recent study introduces a groundbreaking method for early crop identification, leveraging the Bayesian Probability Update Model (BPUM). This innovative approach combines historical planting data ...

Brazilian Journal of Probability and Statistics, Vol. 27, No. 1 (February 2013), pp. 1-19 (19 pages) We introduce a Bayesian analysis for beta generalized distributions and related exponentiated ...

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 ...

We develop novel methods to make Bayesian inference more efficient, scalable, and practical. This includes work on variational methods, Monte Carlo algorithms, and techniques for handling complex ...