BITESIZE | Exploring Dynamic Regression Models, with David Kohns
Learning Bayesian Statistics
00:00
Understanding Variable Selection and Dynamic Regression Models
This chapter explores variable and component selection in dynamic regression models, emphasizing projective-predictive inference. It highlights the complexities in choosing surrogate versus full models and examines the role of R-square priors in causal analyses.
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