Most chatter about AI in other than research and academic institutions is about Machine Learning (ML) and various forms of neural nets and deep learning. Natural Language (speech recognition, language ...

In my practice, I find most people involved with advanced analytics, such as predictive, data science, and ML, are familiar with the name Bayes, and can even reproduce the simple theorem below. Still, ...

The past decade has witnessed significant advances in causal inference and Bayesian network learning, two intertwined disciplines that allow researchers to discern underlying cause‐and‐effect ...

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 ...

In the ever-evolving toolkit of statistical analysis techniques, Bayesian statistics has emerged as a popular and powerful methodology for making decisions from data in the applied sciences. Bayesian ...

"The more extraordinary the event, the greater the need for it to be supported by strong proofs." -- Pierre Simon Laplace (1814) stating a non-controversial principle of rational inference When the ...

To meet the Basel II regulatory requirements for the advanced measurement approaches, the bank’s internal model must include the use of internal data, relevant external data, scenario analysis and ...