The application of Bayesian methods to large-scale phylogenetics problems is increasingly limited by computational issues, motivating the development of methods that can complement existing Markov ...

Bayesian inference provides a robust framework for combining prior knowledge with new evidence to update beliefs about uncertain quantities. In the context of statistical inverse problems, this ...

As does Woodroofe, we consider a Bayesian sequential allocation between two treatments that incorporates a covariate. The goal is to maximize the total discounted expected reward from an infinite ...

The increasing interest in Bayesian group sequential design is due to its potential to reinforce efficiency in clinical trials, shorten drug development time, and enhance the accuracy of statistical ...

In the Big Data era, many scientific and engineering domains are producing massive data streams, with petabyte and exabyte scales becoming increasingly common. Besides the explosive growth in volume, ...