| A MOSUM procedure for the estimation of multiple random change points B Eichinger, C Kirch | 152* | 2018 |
| Evaluating stationarity via change-point alternatives with applications to fMRI data JAD Aston, C Kirch The Annals of Applied Statistics, 2012 | 129* | 2012 |
| Detection of changes in multivariate time series with application to EEG data C Kirch, B Muhsal, H Ombao Journal of the American Statistical Association 110 (511), 1197-1216, 2015 | 111 | 2015 |
| Detecting and estimating changes in dependent functional data JAD Aston, C Kirch Journal of Multivariate Analysis 109, 204-220, 2012 | 108 | 2012 |
| TFT-bootstrap: Resampling time series in the frequency domain to obtain replicates in the time domain C Kirch, DN Politis | 90 | 2011 |
| Changepoints in times series of counts J Franke, C Kirch, JT Kamgaing Journal of Time Series Analysis 33 (5), 757-770, 2012 | 78 | 2012 |
| Bootstrapping sequential change-point tests for linear regression M Hušková, C Kirch Metrika 75 (5), 673-708, 2012 | 66 | 2012 |
| Bootstrapping confidence intervals for the change‐point of time series M Hušková, C Kirch Journal of Time Series Analysis 29 (6), 947-972, 2008 | 66 | 2008 |
| On the detection of changes in autoregressive time series, II. Resampling procedures M Hušková, C Kirch, Z Prášková, J Steinebach Journal of Statistical Planning and Inference 138 (6), 1697-1721, 2008 | 66 | 2008 |
| Resampling methods for the change analysis of dependent data C Kirch kups.ub.uni-koeln.de, 2006 | 65 | 2006 |
| On the use of estimating functions in monitoring time series for change points C Kirch, JT Kamgaing Journal of Statistical Planning and Inference 161, 25-49, 2015 | 54* | 2015 |
| Bootstrapping sequential change-point tests C Kirch Sequential Analysis 27 (3), 330-349, 2008 | 54 | 2008 |
| Modified sequential change point procedures based on estimating functions C Kirch, S Weber | 50 | 2018 |
| mosum: Moving sum based procedures for changes in the mean A Meier, H Cho, C Kirch R package version 1 (2), 5, 2021 | 48* | 2021 |
| Block permutation principles for the change analysis of dependent data C Kirch Journal of Statistical Planning and Inference 137 (7), 2453-2474, 2007 | 46 | 2007 |
| High dimensional efficiency with applications to change point tests JAD Aston, C Kirch | 45* | 2018 |
| Testing for parameter stability in nonlinear autoregressive models C Kirch, JT Kamgaing Journal of Time Series Analysis 33 (3), 365-385, 2012 | 40 | 2012 |
| Detecting changes in the covariance structure of functional time series with application to fMRI data C Stoehr, JAD Aston, C Kirch Econometrics and Statistics 18, 44-62, 2021 | 39 | 2021 |
| Data segmentation algorithms: Univariate mean change and beyond H Cho, C Kirch Econometrics and Statistics, 2021 | 36 | 2021 |
| Monitoring changes in the error distribution of autoregressive models based on Fourier methods Z Hlávka, M Hušková, C Kirch, SG Meintanis Test 21, 605-634, 2012 | 36 | 2012 |
John AstonStatistical Laboratory, DPMMS, University of CambridgeVerified email at statslab.cam.ac.uk
