BITESIZE | Hacking Bayesian Models for Better Performance, with Luke Bornn
Learning Bayesian Statistics
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Navigating Complexities in Bayesian Modeling and Computation
This chapter delves into the intricacies of Bayesian modeling, particularly the selective conditioning on variables during posterior sampling. It highlights the difficulties encountered with standard libraries and the necessity of understanding various computational strategies for effective model fitting.
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