Bayesian approaches to variable selection and model comparison construct a coherent probabilistic framework that integrates prior beliefs with observed data. In variable selection, each candidate ...

Offered through an interdisciplinary partnership, data science at CU Boulder is delivered by the Departments of Applied Mathematics, Computer Science, and Information Science and awarded by the ...

Bayesian quantile regression extends the classical quantile regression framework by embedding it within a probabilistic paradigm, allowing direct inference on conditional quantiles through ...

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 ...