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Lotte_CBA is a project using customer data from the Lotte Competition. This project recommend personal products to each customer individually by analyzing recommmendation system, and offer services for store management.
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LAWS is the thesis presented in a large-scale inference (spring, 2021) in UOS.
The presentation is a summary of the paper Cai, T. T., Sun, W., & Xia, Y. (2021). LAWS: A locally adaptive weighting and screening approach to spatial multiple testing. Journal of the American Statistical Association, 1-14. I learned from the book Efron, B. (2012). Large-scale inference: empirical Bayes methods for estimation, testing, and prediction (Vol. 1). Cambridge University Press.
- fusion is the final-project presented in a Multivariate statistics (autumn, 2021) in UOS.
The presentation is a summary of the paper Stokell, B. G., Shah, R. D., & Tibshirani, R. J. (2021). Modelling high‐dimensional categorical data using nonconvex fusion penalties. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 83(3), 579-611. I learned from the book Hastie, T., Tibshirani, R., Friedman, J. H., & Friedman, J. H. (2009). The elements of statistical learning: data mining, inference, and prediction (Vol. 2, pp. 1-758). New York: springer.
- AISR is the final-project presented in a Topics in statistics (autumn, 2021) in UOS.
As an application of Importance Sampling, the Importance Sampling method was used to estimate the probability of rare events in regression analysis. I learned from the book Rubinstein, R. Y., & Kroese, D. P. (2016). Simulation and the Monte Carlo method. John Wiley & Sons.