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 ...

Specialization: Bayesian Statistics for Data Science Instructor: Brian Zaharatos Prior knowledge needed: Statistics View on Coursera Learning Outcomes Articulate the primary interpretations of ...

Description This course offers a rigorous yet practical exploration of Bayesian reasoning for data-driven inference and decision-making. Students will gain a deep understanding of probabilistic ...

The method is based on Bayesian inference, a statistical framework that estimates the most likely state of a system using observed data.

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, ...

Christopher J. Fallaize, Peter J. Green, Kanti V. Mardia, Stuart Barber, Bayesian protein sequence and structure alignment, Journal of the Royal Statistical Society.