This article proposes a robust Bayesian approach to regression for modelling continuous, strictly positive, and asymmetric biomedical data. The methodology is based on log-symmetric distributions, ...

Selecting prior distributions in Bayesian regression analysis is a challenging task. Even if knowledge already exists, gathering this information and translating it into informative prior ...

Articulate the primary interpretations of probability theory and the role these interpretations play in Bayesian inference Use Bayesian inference to solve real-world statistics and data science ...

New FDA guidance on the use of Bayesian statistics signals a broader shift in accommodating more flexible clinical trial ...

Uncertainty quantification (UQ) is a field of study that focuses on understanding, modeling, and reducing uncertainties in computational models and real-world systems. It is widely used in engineering ...