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Bayesian Computation Research Project. Mentored by Prof. Steven A. Culpepper

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Bayesian-Computation-Project

Research

  • Engaged in a comprehensive project aiming to master Bayesian methods for regression models, especially when dealing with binary or polytomous outcome variables, or multiple outcome variables in R studio
  • Analyzed heart-attack dataset and applied advanced techniques, Cumulative Link Model, Hamiltonian Monte Carlo, Horseshoe Prior to establishing Bayesian model and making prediction

Conclusion

  • Bayesian model with horseshoe prior performs the best
  • 1 (male) is associated with the log odds decrease in the outcome by 1.64 - Female is more likely to get heart attack. Typical chest pain would have a higher impact on the outcome variable compared to other type of chest pains.

Members

  • Haiyue Zhang, Wendy Zheng, Ishaan Bhandari, Kehuan Wang, April Wu

Mentor

  • Professor Steven A. Culpepper

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Bayesian Computation Research Project. Mentored by Prof. Steven A. Culpepper

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