311 citations · 447 across the 20 of their papers we have counts for
4 papers · 1 filter
Optimal Test-Data Piling in HDLSS Classification with Covariance Heterogeneity
Taehyun Kim, Jeongyoun Ahn, Sungkyu Jung
This work addresses a longstanding question in high-dimensional linear classification: Is perfect classification achievable in heterogeneous covariance structures? We focus on the…
Adjusting systematic bias in high dimensional principal component scores
Sungkyu Jung
Principal component analysis continues to be a powerful tool in dimension reduction of high dimensional data. We assume a variance-diverging model and use the high-dimension, low-s…
Inference on subspheres model for directional data
Sungkyu Jung
Modeling deformations of a real object is an important task in computer vision, biomedical engineering and biomechanics. In this paper, we focus on a situation where a three-dimens…
PCA consistency in high dimension, low sample size context
Sungkyu Jung, J. S. Marron
Principal Component Analysis (PCA) is an important tool of dimension reduction especially when the dimension (or the number of variables) is very high. Asymptotic studies where the…