A MOSUM procedure for the estimation of multiple random change points B Eichinger, C Kirch | 176* | 2018 |
Evaluating stationarity via change-point alternatives with applications to fMRI data JAD Aston, C Kirch The Annals of Applied Statistics, 2012 | 137* | 2012 |
Detecting and estimating changes in dependent functional data JAD Aston, C Kirch Journal of Multivariate Analysis 109, 204-220, 2012 | 125 | 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 | 117 | 2015 |
TFT-bootstrap: Resampling time series in the frequency domain to obtain replicates in the time domain C Kirch, DN Politis | 94 | 2011 |
Changepoints in times series of counts J Franke, C Kirch, JT Kamgaing Journal of Time Series Analysis 33 (5), 757-770, 2012 | 82 | 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 | 70 | 2008 |
Bootstrapping sequential change-point tests for linear regression M Hušková, C Kirch Metrika 75 (5), 673-708, 2012 | 67 | 2012 |
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 | 66 | 2006 |
mosum: Moving sum based procedures for changes in the mean A Meier, H Cho, C Kirch R package version 1 (2), 5, 2021 | 58* | 2021 |
Bootstrapping sequential change-point tests C Kirch Sequential Analysis 27 (3), 330-349, 2008 | 55 | 2008 |
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 |
Modified sequential change point procedures based on estimating functions C Kirch, S Weber | 51 | 2018 |
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 | 50 | 2021 |
Block permutation principles for the change analysis of dependent data C Kirch Journal of Statistical Planning and Inference 137 (7), 2453-2474, 2007 | 49 | 2007 |
Data segmentation algorithms: Univariate mean change and beyond H Cho, C Kirch Econometrics and Statistics 30, 76-95, 2024 | 47 | 2024 |
High dimensional efficiency with applications to change point tests JAD Aston, C Kirch | 47* | 2018 |
Two-stage data segmentation permitting multiscale change points, heavy tails and dependence H Cho, C Kirch Annals of the Institute of Statistical Mathematics, 1-32, 2022 | 45* | 2022 |
Testing for parameter stability in nonlinear autoregressive models C Kirch, JT Kamgaing Journal of Time Series Analysis 33 (3), 365-385, 2012 | 44 | 2012 |