Discover how credibility theory helps actuaries use historical data to estimate risks and set insurance premiums; learn how ...

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 ...

Bayesian methods in Structural Equation Modeling (SEM) represent a paradigm shift in statistical analysis, integrating prior beliefs with empirical data to derive robust parameter estimates. This ...

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 ...

This study presents a Bayesian parametric model for the purpose of estimating the extreme load on a wind turbine. The extreme load is the highest stress level imposed on a turbine structure that the ...

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 ...

An approximate Bayesian method is developed to study the joint mortality rate of two cancer sites over several geographic areas. A conditionally independent two-stage hierarchical model is used to ...