11 citations · 16 across the 6 of their papers we have counts for
6 papers
Moving sum procedure for change point detection under piecewise linearity
Joonpyo Kim, Hee-Seok Oh, Haeran Cho
We propose a computationally and statistically efficient procedure for segmenting univariate data under piecewise linearity. The proposed moving sum (MOSUM) methodology detects mul…
Lévy Adaptive B-spline Regression via Overcomplete Systems
Sewon Park, Hee-Seok Oh, Jaeyong Lee
The estimation of functions with varying degrees of smoothness is a challenging problem in the nonparametric function estimation. In this paper, we propose the LABS (Lévy Adaptive…
Multi-feature Clustering of Step Data using Multivariate Functional Principal Component Analysis
Wookyeong Song, Hee-Seok Oh, Yaeji Lim +1
This paper presents a new statistical method for clustering step data, a popular form of health record data easily obtained from wearable devices. Since step data are high-dimensio…
Robust Geodesic Regression
Ha-Young Shin, Hee-Seok Oh
This paper studies robust regression for data on Riemannian manifolds. Geodesic regression is the generalization of linear regression to a setting with a manifold-valued dependent…
Spherical Principal Curves
Jang-Hyun Kim, Jongmin Lee, Hee-Seok Oh
This paper presents a new approach for dimension reduction of data observed in a sphere. Several dimension reduction techniques have recently developed for the analysis of non-Eucl…
Ensemble Patch Transformation: A New Tool for Signal Decomposition
Donghoh Kim, Guebin Choi, Hee-Seok Oh
This paper considers the problem of signal decomposition and data visualization. For this purpose, we introduce a new multiscale transform, termed `ensemble patch transformation' t…