Bayesian Paper Reviews

This repository contains presentation slides and summaries for reviews of three Bayesian analysis papers. Each presentation provides a summary and key insights from the paper, focusing on the Bayesian methods used.

Papers Reviewed

1. Shotgun Stochastic Search for “Large p” Regression

   • Type: Team Project
   • Achievement: Achieved the top score among teams.
   • Authors: Hans, C., Dobra, A., & West, M.
   • Journal: Journal of the American Statistical Association
   • Volume: 102, Issue: 478, Pages: 507–516
   • Shotgun_Stochastic_Search_Large_p_Regression/Shotgun_Stochastic_Search_Large_p_Regression.pdf
   • Team Members: Nayeon Kwon, Yejin Jeong
   • Achievement Details: Our team was awarded the top score for this project, reflecting our deep understanding of the Bayesian methods discussed.

2. Bayesian Quantile Regression for Longitudinal Studies with Nonignorable Missing Data

   • Type: Team Project
   • Grade: A+ for this team project.
   • Authors: Yuan, Y., & Yin, G.
   • Journal: Biometrics
   • Volume: 66, Issue: 1, Pages: 105–114
   • Bayesian_Quantile_Regression_Longitudinal_Studies/Bayesian_Quantile_Regression_Longitudinal_Studies.pdf
   • Additional Resources:
     • Review Summary in Korean
   • Team Members: Nayeon Kwon, Hyunwoo Im
   • Grade Details: Received an A+ grade, demonstrating our effective team collaboration and in-depth analysis.

3. A Bayesian Localized Conditional Autoregressive Model for Estimating the Health Effects of Air Pollution

   • Type: Individual Project
   • Grade: A+ for this individual project.
   • Authors: Lee, D., Rushworth, A., & Sahu, S. K.
   • Journal: Biometrics
   • Volume: 70, Issue: 2, Pages: 419–429
   • Bayesian_Localized_CAR_Health_Effects_Air_Pollution/Bayesian_Localized_CAR_Health_Effects_Air_Pollution.pdf
   • Additional Resources:
     • Review Summary in Korean
   • Grade Details: Achieved an A+ grade, reflecting my strong individual performance and thorough understanding of the Bayesian methods.

References

1. Yuan, Y., & Yin, G. (2009). Bayesian Quantile Regression for Longitudinal Studies with Nonignorable Missing Data. Biometrics, 66(1), 105–114.
2. Hans, C., Dobra, A., & West, M. (2007). Shotgun Stochastic Search for “Large p” Regression. Journal of the American Statistical Association, 102(478), 507–516.
3. Lee, D., Rushworth, A., & Sahu, S. K. (2014). A Bayesian Localized Conditional Autoregressive Model for Estimating the Health Effects of Air Pollution. Biometrics, 70(2), 419–429.
4. Lee, D. (2017). Carbayes version 4.6: An R package for spatial areal unit modelling with conditional autoregressive priors. Glasgow: University of Glasgow.

About

These presentations and summaries were created as part of my coursework on Bayesian methods. They demonstrate my ability to analyze and communicate complex statistical techniques. The repository includes a summary in Korean, showcasing my bilingual abilities and further analysis.

License

This project is licensed under the MIT License. See the LICENSE.txt file for details.