Last updated: September 4, 2026
1. Jeehyun Hwang and Sungkyu Jung, “Dense Diversification or Sparse Allocation? Evidence from High-Dimensional Minimum Variance Portfolios,” accepted for publication in Communications for Statistical Applications and Methods.
1. Jeehyun Hwang, Dongsun Yoon, Sungkyu Jung, Min-Jeong Park and Inkwon Yeo (2026), “iLBA: An R package for confidentially disseminating aggregated frequency tables,” SoftwareX Volume 35, September 2026, 102880. (arXiv) (link)
2. Sujin Lee and Sungkyu Jung (2026). “Debiased Group Lasso for Multiple Compositional Data,” Annals of the Institute of Statistical Mathematics 78, 627–651. (link)
3. Jaesung Park and Sungkyu Jung (2026), “Generalized Frechet means with random minimizing domains and its strong consistency”, Biometrika 113(1), asag002. (link) (arXiv)
4. Minwoo Kim and Sungkyu Jung (2025), “Robust and Differentially Private Principal Component Analysis,” Statistical Analysis and Data Mining: An ASA Data Science Journal 18(6) e70053. (link) (arXiv)
5. Minwoo Kim, Sangil Han, Jeongyoun Ahn and Sungkyu Jung (2025). “Variable selection and basis learning for ordinal classification,” Journal of Computational and Graphical Statistics 34(4) 1432-1445. (arXiv) (link)
6. Dongsun Yoon and Sungkyu Jung (2025). “Adaptive Reference-Guided Estimation of Principal Component Subspace in High Dimensions,” Stat 14:e70081. (link)
7. Sangil Han, Kyoowon Kim and Sungkyu Jung (2025). “Subspace Recovery in Winsorized PCA: Insights into Accuracy and Robustness,” Proceedings of The 28th Int. Conf. Artif. Intell. Statist. (AISTATS 2025), PMLR 258:3061-3069. (arXiv) (pdf)
8. Donghyeok Jo and Sungkyu Jung (2025). “Inference on the shape of densities on Riemannian manifolds via SiZer”, Journal of Korean Statistical Society, 54, 442-477. (pdf) (link) (software)
9. Minwoo Kim, Jonghyeok Lee, Seung Woo Kwak, and Sungkyu Jung (2025). “Differentially Private Multivariate Statistics with an Application to Contingency Table Analysis,” Electronic Journal of Statistics 19(1) 1507-1569. (arXiv) (link)
10. Kipoong Kim, Jaesung Park, and Sungkyu Jung (2024). “Principal component analysis for zero-inflated compositional data”, Computational Statistics and Data Analysis 198, October, 107989. (link) (software)
11. Taehyun Kim, Woonyoung Chang, Jeongyoun Ahn, and Sungkyu Jung (2024). “Double Data Piling: A High-Dimensional Solution for Asymptotically Perfect Multi-Category Classification” Journal of Korean Statistical Society 53, 704-737. (link) (pdf)
12. Sangil Han, Kyoowon Kim and Sungkyu Jung (2024). “Robust SVD Made Easy: A fast and reliable algorithm for large-scale data analysis,” Proceedings of The 27th Int. Conf. Artif. Intell. Statist. (AISTATS 2024), PMLR 238:1765-1773. (arXiv) (pdf)
13. Sujin Lee and Sungkyu Jung (2024). “Variable Selection and Inference Strategies for Multiple Compositional Regression,” Chemometrics and Intelligent Laboratory Systems 248, May, 105121. (link)
14. Sangil Han, Minwoo Kim, Sungkyu Jung and Jeongyoun Ahn (2024). “Sparse Ordinal Discriminant Analysis,” Biometrics 80(1), March, ujad040. (link)
15. Seung Woo Kwak and Sungkyu Jung (2024). “Highly-private large-sample tests for contingency tables”, Stat 13:e658. (link) (pdf)
16. Kipoong Kim and Sungkyu Jung (2024). “Integrative sparse reduced-rank regression via orthogonal rotation for analysis of high-dimensional multi-source data,” Statistics and Computing 34, #2. (link) (pdf) (software)
17. Changjo Yu, Sungkyu Jung and Jisu Kim (2023), “Significance of Modes in the Torus by Topological Data Analysis,” Stat 12:e636. (link)
18. An, S., Doan, T., Lee, J., Kim, J., Kim, YJ., Kim, Y., Yoon, C., Jung, S., Kim, D., Kwon, S., Kim, HJ., Ahn, J., and Park, C. (2023). “A Comparison of Synthetic Data Approaches Using Utility and Disclosure Risk Measures”, The Korean Journal of Applied Statistics 36(2), 141-166. (pdf)
19. Sujin Lee, Sungkyu Jung, Jeferson Lourenco, Dean Pringle, and Jeongyoun Ahn (2023). “Resampling-based Inferences for Compositional Regression with Application to Beef Cattle Microbiomes”, Statistical Methods in Medical Research, 32(1), 151-164. (link)
20. Seungki Hong and Sungkyu Jung (2022). “ClusTorus: An R package for prediction and clustering on the torus by conformal prediction”, The R Journal, 14(2), 186-207. (link)
21. Juhee Son, Min-jeong Park and Sungkyu Jung (2022). “A Parametric Bootstrap Test for Comparing Differentially Private Histograms”. The Korean Journal of Applied Statistics 35(1), 1-17. (pdf)
22. Woonyoung Chang, Jeongyoun Ahn and Sungkyu Jung (2021). “Double data piling leads to perfect classification”. Electronic Journal of Statistics 15(2): 6382-6428. (link)
1. Changwon Yoon, Minwoo Kim, Sungkyu Jung and Jeongyoun Ahn. “Joint estimation of high-dimensional spiked covariance matrices via a partially shared subspace,” manuscript. (arXiv)
2. Yongjae Kim, Jiwoo Kim and Sungkyu Jung. “A unified framework for measuring attribute disclosure risks in synthetic data,” manuscript.
3. Kyoowon Kim and Sungkyu Jung. “Testing and segmentation of joint and individual components in integrative multi-source factor models,” manuscript.
4. Jihyun Ryu, Jongmin Lee and Sungkyu Jung. “M-estimation on Riemannian Manifolds: Efficiency, Calibration and Computation,” manuscript.
5. Yongjae Kim, Haeun Moon and Sungkyu Jung. “An Association Measure for Mixed-Types Variables,” manuscript.
6. Chihoon Lee, Sungkyu Jung and Hyokyung G. Hong. “Predicting current outcomes from historical survey data with weighted conformal prediction,” manuscript.
7. Kyungjin Shin, Hyunsu Yu, Yongjae Kim, Giheon Seong, Changwon Yoon, Jeongyoun Ahn, Sungkyu Jung, and Cheolwoo Park. “A Comprehensive Analysis of Utility and Disclosure Risk Metrics for Synthetic Data,” manuscript.
8. Minwoo Kim, Junyong Park and Sungkyu Jung. “Enhanced Differentially Private Mechanisms via Empirical Bayes,” manuscript.
9. Jaesung Park and Sungkyu Jung. “Wasserstein-Quantile PCA,” manuscript in progress.
10. Taehyun Kim, Jeongyoun Ahn and Sungkyu Jung. “Optimal Test-Data Piling in HDLSS Classification with Covariance Heterogeneity,” manuscript. (An old version is available at arXiv.)
11. SeoWon Choi and Sungkyu Jung. “Integrative decomposition of multi-source data by identifying partially-joint score subspaces,” manuscript. (arXiv)
12. Minwoo Kim and Sungkyu Jung. “Non-asymptotic error bound for sparse low-rank structured GEP”, manuscript.
1. The dppca R package provides tools for differentially private PCA visualizations, written by Yejin and Minwoo.
2. The iLBA R package provides tools for the confidential dissemination of aggregated frequency tables from microdata, written by Jeehyun and Dongsun.
3. The ClusTorus R package provides tools for mixture model-based clustering of multivariate angular data, written by Seungki Hong.
4. Recently developed software can be found at GitHub repo
5. Old pieces of software can be found at here