Modern Multivariate Statistics
High-dimension, low-sample-size (HDLSS) analysis
Statistics for unconventional, non-Euclidean, manifold-valued and/or multi-sourced data
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.
Zhao Ren, Sungkyu Jung and Xingye Qiao (2022). “Covariance-engaged Classification of Sets via Linear Programming”, *Statistica Sinica* 32, 1515-1540.
Sungkyu Jung (2022). “Adjusting systematic bias in high dimensional principal component scores”, *Statistica Sinica* 32, 939-959.
Sungkyu Jung, Kiho Park and Byungwon Kim (2021). “Clustering on the torus by conformal prediction”, *Annals of Applied Statistics*. Vol. 15, No. 4, 1583-1603.
Woonyoung Chang, Jeongyoun Ahn and Sungkyu Jung (2021). “Double data piling leads to perfect classification”. *Electronic Journal of Statistics* 15(2): 6382-6428.
Sungkyu Jung (2021). “Geodesic projection of the von Mises-Fisher distribution for projection pursuit of directional data”, Electronic Journal of Statistics 15(1): 984-1033.
Byungwon Kim, Joern Schulz and Sungkyu Jung (2020). “Kurtosis test of modality for rotationally symmetric distributions on hyperspheres”, The Journal of Multivariate Analysis, 178, Article 104603.
Byungwon Kim, Stephan Huckemann, Joern Schulz, and Sungkyu Jung (2019). “Small sphere distributions for directional data with application to medical imaging”, Scandinavian Journal of Statistics. 46(4) 1047-1071.
Sungkyu Jung, Jeongyoun Ahn, and Yongho Jeon (2019). “Penalized Orthogonal Iteration for Sparse Estimation of Generalized Eigenvalue Problem” Journal of Computational and Graphical Statistics. 28(3) 710-721.
Sungkyu Jung, Myung Hee Lee and Jeongyoun Ahn (2018). “On the number of principal components in high dimensions,” Biometrika 105(2), 389-402.
Sungkyu Jung (2018). “Continuum directions for supervised dimension reduction,” Computational Statistics and Data Analysis 125, 27-43.
Gen Li and Sungkyu Jung (2017). “Incorporating Covariates into Integrated Factor Analysis of Multi-View Data,” Biometrics 73 (4), 1433-1442.
David Groisser, Sungkyu Jung, and Armin Schwartzman (2017). “Geometric foundations for statistics on symmetric positive definite matrices: characterizations of minimal scaling-rotation curves in low dimensions”, Electronic Journal of Statistics, Vol. 11, No. 1, 1092-1159.
Sungkyu Jung, Armin Schwartman and David Groisser (2015). “Scaling-rotation distance and interpolation of symmetric positive-definite matrices”. SIAM. J. Matrix Anal. & Appl. 36-3, pp. 1180-1201
Joern Schulz, Sungkyu Jung, Stephan Huckemann, Michael Pierrynowski, J. S. Marron, Stephen M. Pizer (2015) “Analysis of rotational motion from directional data”. Journal of Computational and Graphical Statistics, 24(2), 539-560.
Sungkyu Jung and Xingye Qiao (2014). “A statistical approach to set classification by feature selection with applications to classification of histopathology images”, Biometrics, 70, 536-545.
Sungkyu Jung, Arusharka Sen and J. S. Marron (2012). “Boundary behavior in high dimension, low sample size asymptotics of PCA”, The Journal of Multivariate Analysis, 109, 190-203.
Sungkyu Jung, Ian L. Dryden and J. S. Marron (2012). “Analysis of Principal Nested Spheres”, Biometrika, 99(3), 551-568.
Sungkyu Jung, Mark Foskey and J. S. Marron (2011). “Principal Arc Analysis on direct product manifolds”, The Annals of Applied Statistics, 5, 578-603.
Sungkyu Jung and J. S. Marron (2009). “PCA consistency in High dimension, low sample size context”. The Annals of Statistics 37, 4104-4130.
Research Award, College of Natural Sciences, Seoul National University
Excellence in Teaching Award, College of Natural Science, Seoul National University
Early Career Development Award, Korean International Statistical Society
US Junior Oberwolfach Fellow, MFO, Germany
Distinguished Paper Award, International Biometric Society/ENAR
Wassily Hoeffding Award, Statistics and Operations Research, University of North Carolina