Research

publications (& software):

S. Kumar, H. Xu, H. Cho and D. Wang (2026+) Estimation and Inference for Change Points in Functional Regression Time Series, Statistica Sinica. - paper - arXiv

M. Barigozzi, H. Cho and H. Maeng (2026) Tail-robust factor modelling of vector and tensor time series in high dimensions, Biometrika, 113(2): asaf093. - paper - arXiv - github

M. Barigozzi, H. Cho and L. Trapani (2026) Moving sum procedure for multiple change point detection in large factor models, Journal of Time Series Analysis, 47(3): 450-464. - paper - arXiv - github

Y. Choi, H. Cho and H. Son (2026) Capturing usage patterns in bike sharing system via multilayer network fused Lasso, Technometrics, 68(1): 96–105. - paper - arXiv

H. Cho, T. Kley and H. Li (2025) Detection and inference of changes in high-dimensional linear regression with non-sparse structures, Journal of the Royal Statistical Society Series B, 87(5): 1528-1552. - paper - arXiv - github

E. McGonigle and H. Cho (2025) Nonparametric data segmentation in multivariate time series via joint characteristic functions, Biometrika, 112(2): asaf024. - paper - arXiv - R package CptNonPar

H. Cho, H. Maeng, I. A. Eckley and P. Fearnhead (2024) High-dimensional time series segmentation via factor-adjusted vector autoregressive modelling, Journal of the American Statistical Association, 119(547): 2038-2050. - paper - arXiv - github

J. Kim, H.-S. Oh and H. Cho (2024) Moving sum procedure for change point detection under piecewise linearity, Technometrics, 66(3): 358-367. - paper - arXiv - github

H. Cho and D. Owens (2024) High-dimensional data segmentation in regression settings permitting heavy tails and temporal dependence, Electronic Journal of Statistics, 18(1): 2620-2664. - paper - arXiv - github

M. Barigozzi, H. Cho and D. Owens (2024) FNETS: Factor-adjusted network estimation and forecasting for high-dimensional time series, Journal of Business & Economic Statistics, 42(3): 890-902. - paper - arXiv - R package fnets * Check the arXiv version for the most up-to-date version with some typos corrected.

H. Cho and C. Kirch (2024) Data segmentation algorithms: Univariate mean change and beyond, Econometrics and Statistics, 30: 76-95. - paper - arXiv

H. Cho and P. Fryzlewicz (2024) Multiple change point detection under serial dependence: Wild contrast maximisation and gappy Schwarz algorithm, Journal of Time Series Analysis, 45(3): 479-494. - paper - arXiv - github - R package breakfast

D. Owens, H. Cho and M. Barigozzi (2023) fnets: An R Package for Network Estimation and Forecasting via Factor-Adjusted VAR Modelling, the R Journal, 15(3): 214-239. - paper - arXiv - R package fnets

E. McGonigle and H. Cho (2023) Robust multiscale estimation of time-average variance for time series segmentation, Computational Statistics and Data Analysis, 179:107648. - paper - arXiv - github

H. Cho and C. Kirch (2022) Bootstrap confidence intervals for multiple change points based on moving sum procedures, Computational Statistics and Data Analysis, 175:107552. - paper - arXiv - R package mosum

H. Cho and C. Kirch (2022) Two-stage data segmentation permitting multiscale change points, heavy tails and dependence, Annals of the Institute of Statistical Mathematics, 74: 653-684. - paper - arXiv - R packages mosum, breakfast 

H. Cho and K. Korkas (2021) High-dimensional GARCH process segmentation with an application to Value-at-Risk, Econometrics and Statistics, 23: 187-203. - paper

A. Meier, C. Kirch and H. Cho (2021) mosum: A package for moving sums in change-point analysis, Journal of Statistical Software, 97: 1-42. - paper - R package mosum

M. Barigozzi and H. Cho (2020) Consistent estimation of high-dimensional factor models when the factor number is over-estimated, Electronic Journal of Statistics, 14: 2892–2921. - paper - arxiv

M. Barigozzi, H. Cho and P. Fryzlewicz (2018) Simultaneous multiple change-point and factor analysis for high-dimensional time series, Journal of Econometrics, 206: 187-225. - paper - R package factorcpt

H. Cho and Y. Yu (2018) Link prediction for inter-disciplinary collaboration via co-authorship network. Social Network Analysis and Mining, 8:25. - paper

H. Cho (2016) A test for second-order stationarity of time series based on unsystematic sub-samples, Stat, 5: 262-277. - paper - R package unsystation

H. Cho (2016) Change-point detection in panel data via double CUSUM statistic, Electronic Journal of Statistics, 10:2000-2038. - paper - R package hdbinseg

H. Cho and P. Fryzlewicz (2015) Multiple change-point detection for high-dimensional time series via Sparsified Binary Segmentation, Journal of the Royal Statistical Society Series B, 77: 475-507. - paper - correction - R package hdbinseg

H. Cho, Y. Goude, X. Brossat and Q. Yao (2013) Modelling and forecasting daily electricity load curves: a hybrid approach, Journal of the American Statistical Association, 108: 7–21. - paper - supplement 

O. Christodoulaki, H. Cho and P. Fryzlewicz (2012) A reflection of history: fluctuations in Greek sovereign risk between 1914 and 1929, European Review of Economic History, 16: 550–571. - paper 

H. Cho and P. Fryzlewicz (2012) High-dimensional variable selection via tilting, Journal of the Royal Statistical Society Series B, 74: 593–622. - paper - R package 

H. Cho and P. Fryzlewicz (2012) Multiscale and multilevel technique for consistent segmentation of nonstationary time series, Statistica Sinica, 22: 207–229. - paper - software - correction 

H. Cho and P. Fryzlewicz (2011) Multiscale interpretation of taut string estimation and its connection to Unbalanced Haar wavelets, Statistics and Computing, 21: 671–681. - paper