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dfm.io | ||
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austinrochford.com
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| | | | | I recently read the interesting paper The ARR2 prior: flexible predictive prior definition for Bayesian auto-regressions on the arXiv and followed its references to the also fascinating Bayesian Regre | |
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twiecki.io
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| | | | | [AI summary] This blog post discusses hierarchical linear regression in PyMC3, highlighting its advantages over non-hierarchical Bayesian modeling. The author explores how hierarchical models can effectively handle multi-level data by leveraging the 'shrinkage-effect', which improves predictions by borrowing strength from related groups. Using the radon dataset, the post compares individual and hierarchical models, demonstrating that the hierarchical approach provides more accurate and robust estimates, especially in cases with limited data. The key takeaway is that hierarchical models balance individual and group-level insights, offering the best of both worlds in data analysis. | |
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bambinos.github.io
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noelwelsh.com
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