Bayesian estimation methods form a dynamic branch of statistical inference, utilising Bayes’ theorem to update probabilities in light of new evidence. This framework combines prior knowledge with ...

Bayesian methods in Structural Equation Modeling (SEM) represent a paradigm shift in statistical analysis, integrating prior beliefs with empirical data to derive robust parameter estimates. This ...

We suggest a new method for integrating volatility information for estimating the value-at-risk and conditional value-at-risk of a portfolio. This new method is developed from the perspective of ...

Extended educational sessions that offer attendees the opportunity to learn research methods and techniques from prominent ...

A research team has developed a new technique to rapidly and accurately determine the charge state of electrons confined in semiconductor quantum dots -- fundamental components of quantum computing ...

The covariance matrix of asset returns is the key input for many problems in finance and economics. This paper introduces a Bayesian nonparametric method to estimate the ex post covariance matrix from ...

Zhang, J., Cao, J., and Wang, L. (2026) Generalized Bayesian Multidimensional Scaling and Model Comparison. Accepted by Statistics and computing. Cao, J., Wu, S ...

What physicians should know about FDA's new proposed guidance ...

Cobimetinib Plus Vemurafenib in Patients With Colorectal Cancer With BRAF Mutations: Results From the Targeted Agent and Profiling Utilization Registry (TAPUR) Study We divided the borrowing ...

This course is available on the MSc in Applied Social Data Science, MSc in Data Science, MSc in Econometrics and Mathematical Economics, MSc in Health Data Science, MSc in Operations Research & ...