Big Data has imposed great challenges for machine learning. Bayesian methods provide a profound framework for characterizing the intrinsic uncertainty and performing probabilistic inference and ...

Bayesian methods have emerged as a pivotal framework in the design and analysis of clinical trials, offering a systematic approach for updating evidence as new data become available.

Scientists have developed a method to identify symmetries in multi-dimensional data using Bayesian statistical techniques. Bayesian statistics has been in the spotlight in recent years due to ...

There are a variety of approaches to Bayesian subgroup analysis. Practitioners should consider the type of subpopulations in which they are interested and choose their methods accordingly. We ...

Carter T. Butts, BAYESIAN META-ANALYSIS OF SOCIAL NETWORK DATA VIA CONDITIONAL UNIFORM GRAPH QUANTILES, Sociological Methodology, Vol. 41 (2011), pp. 257-298 ...

Ecologists are increasingly familiar with Bayesian statistical modeling and its associated Markov chain Monte Carlo (MCMC) methodology to infer about or to discover interesting effects in data. The ...

Bayesian information borrowing is an indispensable part of these designs, which shows great advantages in improving the efficiency of clinical trials. Bayesian methods provide an effective framework ...

In any case, my focus here is not on the pretty maps but rather on the modeling technology–the impressive ability of Bayesian data analysis to give reasonable estimates for all these subgroups.