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 ...

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 ...

Bayesian trials formally integrate prior evidence with accruing data to yield posterior probabilities, supporting interim learning, adaptive modifications, and direct predictive futility/efficacy ...