| Multiple change-point detection for high-dimensional time series via Sparsified Binary Segmentation H Cho, P Fryzlewicz Journal of the Royal Statistical Society: Series B 77 (2), 475-507, 2015 | 382 | 2015 |
| Change-point detection in panel data via double CUSUM statistic H Cho Electronic Journal of Statistics 10, 2000-2038, 2016 | 150 | 2016 |
| Modeling and forecasting daily electricity load curves: a hybrid approach H Cho, Y Goude, X Brossat, Q Yao Journal of the American Statistical Association 108 (501), 7-21, 2013 | 141 | 2013 |
| Simultaneous multiple change-point and factor analysis for high-dimensional time series M Barigozzi, H Cho, P Fryzlewicz The Journal of Econometrics, 2018 | 111 | 2018 |
| High dimensional variable selection via tilting H Cho, P Fryzlewicz Journal of the Royal Statistical Society: Series B 74 (3), 593-622, 2012 | 100 | 2012 |
| Multiscale and multilevel technique for consistent segmentation of nonstationary time series H Cho, P Fryzlewicz Statistica Sinica 22 (1), 207-229, 2012 | 99 | 2012 |
| Link prediction for interdisciplinary collaboration via co-authorship network H Cho, Y Yu Social Network Analysis and Mining 8, 1-12, 2018 | 45 | 2018 |
| mosum: A package for moving sums in change point analysis A Meier, C Kirch, H Cho Journal of Statistical Software 97 (8), 1-42, 2021 | 41 | 2021 |
| Data segmentation algorithms: Univariate mean change and beyond H Cho, C Kirch Econometrics and Statistics, 2021 | 36 | 2021 |
| Two-stage data segmentation permitting multiscale change points, heavy tails and dependence H Cho, C Kirch arXiv preprint arXiv:1910.12486, 2020 | 33* | 2020 |
| A reflection of history: fluctuations in Greek sovereign risk between 1914 and 1929 O Christodoulaki, H Cho, P Fryzlewicz European Review of Economic History 16 (4), 550-571, 2012 | 29 | 2012 |
| Multiscale interpretation of taut string estimation and its connection to Unbalanced Haar wavelets H Cho, P Fryzlewicz Statistics and computing 21, 671-681, 2011 | 25 | 2011 |
| Consistent estimation of high-dimensional factor models when the factor number is over-estimated M Barigozzi, H Cho | 19 | 2020 |
| Multiple change point detection under serial dependence: Wild contrast maximisation and gappy Schwarz algorithm H Cho, P Fryzlewicz Journal of Time Series Analysis, 2023 | 18 | 2023 |
| Modelling and forecasting daily electricity load via curve linear regression H Cho, Y Goude, X Brossat, Q Yao Modeling and Stochastic Learning for Forecasting in High Dimension, Lecture …, 2014 | 17 | 2014 |
| FNETS: Factor-adjusted network estimation and forecasting for high-dimensional time series M Barigozzi, H Cho, D Owens Journal of Business & Economic Statistics, 1-13, 2023 | 14 | 2023 |
| Breakfast: methods for fast multiple change-point detection and estimation A Anastasiou, Y Chen, H Cho, P Fryzlewicz R package version 2 (1), 2020 | 13 | 2020 |
| High-dimensional time series segmentation via factor-adjusted vector autoregressive modeling H Cho, H Maeng, IA Eckley, P Fearnhead Journal of the American Statistical Association, 1-13, 2023 | 12 | 2023 |
| mosum: Moving sum based procedures for changes in the mean A Meier, H Cho, C Kirch R package version 1 (2), 5, 2021 | 12 | 2021 |
| Bootstrap confidence intervals for multiple change points based on moving sum procedures H Cho, C Kirch Computational Statistics & Data Analysis 175, 107552, 2022 | 11 | 2022 |
Claudia KirchInstitute for Mathematical Stochastics, Otto-von-Guericke University MagdeburgAdresse e-mail validée de ovgu.de
