Approximate Bayesian computation (ABC) constitutes a family of likelihood-free methods that have emerged as a cornerstone in statistical inference for complex models where evaluation of the likelihood ...

Bayesian inference in phylogenetic dynamics integrates genetic data with models of evolutionary and population processes to reconstruct the history and tempo of lineage diversification. By combining ...

This course introduces the theoretical, philosophical, and mathematical foundations of Bayesian Statistical inference. Students will learn to apply this foundational knowledge to real-world data ...

This paper develops new econometric methods to infer hospital quality in a model with discrete dependent variables and non-random selection. Mortality rates in patient discharge records are widely ...

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Bayesian networks have become popular tools for enterprise data scientists working with prediction, as the rise of cheap and abundant cloud computing has made way for adaptable infrastructure. In the ...