Bayesian methods have significantly enhanced the analysis of complex data structures, such as semicontinuous outcomes and zero-inflated observations, by providing coherent inferences and more ...

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 ...

Observational data, although readily available, is sensitive to biases such as confounding by indication. Structure learning algorithms for Bayesian Networks (BNs) can be used to discover the ...

Silvia Montagna, Tor Wager, Lisa Feldman Barrett, Timothy D. Johnson, Thomas E. Nichols, Spatial Bayesian Latent Factor Regression Modeling of Coordinate-Based Meta-Analysis Data, Biometrics, Vol. 74, ...

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 ...

Censored survival data is prevalent in such studies. In this article we introduce a Bayesian variable selection procedure that uses a mixture prior composed of a point mass at zero and an inverse ...