The main focus of this short course will be the Bayesian aspect of it. That means this is a slightly more advanced course requiring some knowledge of basic probability, regression methods, and the R ...

We discuss two methods of making nonparametric Bayesian inference on probability measures subject to a partial stochastic ordering. The first method involves a nonparametric prior for a measure on ...

It’s estimated that human adults make about 35,000 decisions a day — the percentage of good decisions depends on the adult. These choices can be as banal as deciding to roll or crumple toilet paper or ...

Bayesian methods have emerged as a pivotal framework in the design and analysis of clinical trials, offering a systematic approach for updating evidence as new data become available. By utilising ...

This is a preview. Log in through your library . Abstract Bayesian statistical inference provides an alternate way to analyze data that is likely to be more appropriate to conservation biology ...

Purpose: Risk assessment is an essential component of genetic counseling and testing, and Bayesian analysis plays a central role in complex risk calculations. We previously developed generalizable ...

Symmetries in nature make things beautiful; symmetries in data make data handling efficient. However, the complexity of identifying such patterns in data has always bedeviled researchers. Scientists ...

Scientists derive a quantum version of Bayes’ rule, bridging classical probability and quantum theory. This breakthrough ...