Bayesian inference has been used for genetic risk calculation. In this traditional method, inheritance events are divided into a number of cases under the inheritance model, and some elements of the ...

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 ...

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 ...

Every utility matrix in a Bayesian decision problem determines a "critical probability" for each of the states of nature: when a critical probability is exceeded, the assessment of the remaining ...

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 ...

We review Bayesian and Bayesian decision theoretic approaches to subgroup analysis and applications to subgroup-based adaptive clinical trial designs. Subgroup analysis refers to inference about ...

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 ...

Having a strong opinion about an issue can make it hard to take in new information about it, or to consider other options when they’re presented. Thankfully, there’s an old rule that can help us avoid ...