Approaches for statistical inference -- The Bayes approach -- Bayesian computation -- Model criticism and selection -- The empirical Bayes approach -- Bayesian design -- Special methods and models -- ...

Empirical Bayesian methods occupy a unique position at the interface of frequentist and Bayesian paradigms by estimating prior distributions directly from observed data. This approach preserves the ...

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...

New FDA guidance on the use of Bayesian statistics signals a broader shift in accommodating more flexible clinical trial ...

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 ...

In today's scientific and industrial fields, high-dimensional data in which numerous variables are observed simultaneously, such as genomic, climate, financial, and sensor data, are rapidly increasing ...

Industry groups and drugmakers want the US Food and Drug Administration (FDA) to explicitly clarify that Bayesian statistical methods can be used for products beyond those intended for children and ...