Bayesian Modeling
Applying Bayesian inference
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I want to model [PHENOMENON] using a Bayesian approach. The available data is [DESCRIPTION]. Explain how to define the priors, build the model with PyMC, interpret the posteriors and credibility intervals, and compare this model to a frequentist approach for this problem.
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Astuce : commencez par un modèle simple, utilisez des priors faiblement informatives (ou justifiées) et vérifiez la convergence des chaînes (R-hat < 1,01, ESS suffisant). Analysez la sensibilité aux priors pour distinguer l’influence des données de celle des hypothèses. Pour la comparaison fréquentiste, insistez sur la différence d’interprétation : intervalle de crédibilité vs confiance, et utilisez des critères type WAIC ou validation croisée plutôt qu’un simple test.
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