Bayesian analysis offers a robust framework for deciphering the intricate dynamics of time series data. By treating unknown parameters as random variables, this approach incorporates prior information ...

Journal of Business & Economic Statistics, Vol. 34, No. 4, Special Issue on Big Data (October 2016), pp. 661-672 (12 pages) Randomized controlled trials play an important role in how Internet ...

Journal of the Royal Statistical Society. Series A (Statistics in Society), Vol. 180, No. 4 (OCTOBER 2017), pp. 1191-1209 (19 pages) Area level models, such as the Fay–Herriot model, aim to improve ...

FDA proposes framework clinical trial designs to guide Bayesian methods, improving efficiency in drug development for rare and pediatric conditions.

Functional safety engineers follow the ISA/IEC 61511 standard and perform calculations based on random hardware failures. These result in very low failure probabilities, which are then combined with ...

We develop methodology to bridge scenario analysis and risk forecasting, leveraging their respective strengths in policy settings. The methodology, rooted in Bayesian analysis, addresses the ...

We review Bayesian and Bayesian decision theoretic approaches to subgroup analysis and applications to subgroup-based adaptive clinical trial designs. Subgroup analysis refers to inference about ...

US FDA issues guidance on modernizing statistical methods for clinical trials: Maryland Wednesday, January 14, 2026, 09:00 Hrs [IST] The US Food and Drug Administration today publ ...

Researchers have employed Bayesian neural network approaches to evaluate the distributions of independent and cumulative ...

The main focus of this short course will be the Bayesian aspect of it. That means this is a slightly more advanced course requiring some knowledge of basic probability, regression methods, and the R ...