Publikationen (Claudia Kirch)

Publications in Refereed Journals

  • The state of cumulative sum sequential change point testing seventy years after Page (with A. Aue). To appear in Biometrika, 2024.
  • Data segmentation for time series based on a general moving sum approach (with K. Reckruehm). To appear in Ann. Inst. Stat. Math., 2023+. (Preprint on arXiv).
  • Posterior consistency for the spectral density of non-Gaussian stationary time series (with Y. Tang, J. Lee, R. Meyer). Scand J Statist, 50(3), 11521182, 2023.  (Preprint on arXiv). The final publication is available here.
  • Bootstrap confidence intervals for multiple change points based on moving sum procedures (with H. Cho). CSDA, 175:107552, 2022. (Preprint on arXiv). The final publication is available here.
  • Asymptotic delay times of sequential tests based on U-statistics for early and late change points (with C. Stoehr). (Preprint on arXiv). J. Statist. Plann. Inf., 221:114-135,  2022. The final publication is available here.
  • Data segmentation algorithms: Univariate mean change and beyond (with H. Cho). To appear in Eco.Stat, 2022. (Preprint on arXiv). The final publication is available here.
  • Two-stage data segmentation permitting multiscale change points, heavy tails and dependence (with H. Cho). (Preprint on arXiv). Ann. Inst. Stat. Math., 74:653-684, 2022. The final publication is available here. Video-Talk.
  • Sequential change point tests based on U-statistics (with C. Stoehr). (Preprint on arXiv). Scand. J. Stat., 49:1184-1214, 2022. The final publication is available here.
  • Moving sum data segmentation for stochastic processes based on invariance (with P. Klein). (Preprint on arXiv). Stat. Sinica,  33:1-20, 2023. The final publication is available here.
  • A novel change point approach for the detection of gas emission sources using remotely contained concentration data (with I. Eckley, S. Weber). (Preprint on arXiv). Ann. Appl. Statist.,14:1258-1284, 2020. The final publication is available at ProjectEuclid.
  • Detecting changes in the covariance structure of functional time series with application to fMRI data (with C. Stoehr, J. Aston). (Preprint on arXiv). Eco.Stat., 18:44-62, 2021. The final publication is available here.
  • Bayesian Nonparametric Analysis of Multivariate Time Series: A Matrix Gamma Process Approach (with A. Meier, R. Meyer),  (Preprint on arXiv)J. Multiv. Anal., 175:104560, 2020. The final publication is available here.
  • mosum: A package for moving sums in change-point analysis (with A. Meier, H. Cho). (Preprint)J. of Stat. Software, 97:1-42, 2021. Video-Talk. The final publication is available here.
  • Beyond Whittle: Nonparametric correction of a parametric likelihood with a focus on Bayesian time series analysis (with M.C. Edwards, A. Meier, R. Meyer). Bayesian Analysis, 14:1037-1073, 2019. (Preprint on arXiv)  The final publication is available at Project Euclid.      
  • High dimensional efficiency with applications to change point tests. Electron. J. Statist., 12:1901-1947, 2018 (with J.A.D. Aston) . (Preprint on arXiv) The final publication is available at Project Euclid.
  • Modified sequential change point procedures based on estimating functions. Electron. J. Statist., 12:1579-1613, 2018 (with S. Weber). (Preprint) The final publication is available at Project Euclid.
  • Moving Fourier analysis for locally stationary processes with the bootstrap in view. J. Time Ser. Anal., 38:895-922, 2017 (with F. Häfner). (Preprint) The final publication is available at Wiley.
  • A MOSUM procedure for the estimation of multiple random change points. Bernoulli, 24:526-564, 2018 (with B. Eichinger (formerly Muhsal)). (Preprint) (Corrections) The final publication is available at Project Euclid. Video-Talk.
  • How much information does dependence between wavelet coefficients contain? JASA, 111:1330-1345, 2016 (with C. Jentsch). (Preprint) The final publication is available at Taylor & Francis Online.
  • On the use of estimating functions in monitoring time series for change points. J. Statist. Plann. Inf., 161:25-49, 2015 (with J. Tadjuidje Kamgaing). (Preprint) The final publication is available at ScienceDirect.com.
  • Detection of changes in multivariate time series with applications to EEG data. JASA, 110:1197-1216, 2015 (with B. Muhsal, H. Ombao). (Preprint) The final publication is available at Taylor & Francis Online.
  • Bootstrap procedures for online monitoring of changes in autoregressive models. Comm. Statist. Simulation Comput., 45:2471-2490, 2016 (with Z. Hlávka, M. Hušková, S. Meintanis). (Preprint) The final publication is available at Taylor & Francis Online.
  • Fourier-type tests involving martingale difference processes. Econometric Reviews, 36:468-492, 2014 (with Z. Hlávka, M. Hušková, S. Meintanis). The final publication is available at Taylor & Francis Online.
  • A uniform central limit theorem for neural network-based autoregressive processes with applications to change-point analysis. Statistics, 48:1187-1201, 2014 (with J. Tadjuidje Kamgaing). (Preprint) The final publication is available at Taylor & Francis Online.
  • Evaluating stationarity via change-point alternatives with applications to fMRI data. Ann. Appl. Statist., 6:1906-1948, 2012 (with J.A.D. Aston). The final publication is available at arXiv, , the supplementary material can be found here.
  • Detecting and estimating epidemic changes in dependent functional data. J. Multiv. Anal., 109:204-220, 2012 (with J.A.D. Aston). The final publication is available at ScienceDirect.com.
  • Changepoints in time series of counts. J. Time Ser. Anal., 33:757-770, 2012 (with J. Franke, J. Tadjuidje Kamgaing). (Preprint) The final publication is available at Wiley.
  • Testing for parameter stability in nonlinear autoregressive models. J. Time Ser. Anal., 33:365-385, 2012 (with J. Tadjuidje Kamgaing). (Preprint) The final publication is available at Wiley.
  • Monitoring changes in the error distribution of autoregressive models based on Fourier methods. TEST, 21:605-634, 2012 (with Z. Hlávka, M. Hušková, S. Meintanis). First published online in 2011. (Preprint) The final publication is available at www.springerlink.com.
  • TFT-Bootstrap: Resampling time series in the frequency domain to obtain replicates in the time domain. Ann. Statist., 39:1427-1470, 2011 (with D. N. Politis). (Paper) (Supplement (detailed proofs))
  • Bootstrapping sequential change-point tests for linear regression. Metrika, 75:673-708, 2012 (with M. Hušková). First published online in 2011. (Preprint) The final publication is available at www.springerlink.com.
  • A note on studentized confidence intervals for the change-point. Comput. Statist., 25:269-289, 2010 (with M. Hušková). (Preprint) (Corrections) The final publication is available at www.springerlink.com.
  • Bootstrapping confidence intervals for the change-point of time-series. J. Time Ser. Anal., 29:947-972, 2008 (with M. Hušková). (Preprint on arXiv)
  • Bootstrapping sequential change-point tests. Seq. Anal., 27:330-349, 2008. (Paper) (Preprint)
  • On the detection of changes in autoregressive time series, II. Resampling procedures. J. Statist. Plann. Inference, 138:1697-1721, 2008 (with M. Hušková, Z. Prašková, J. Steinebach). (Preprint)
  • Resampling in the frequency domain of time series to determine critical values for change-point tests. Statistics and Decision, 25:237-261, 2007. (Preprint)
  • Block permutation principles for the change analysis of dependent data. J. Statist. Plann. Inference, 137:2453-2474, 2007. (Preprint)
  • Permutation principles for the change analysis of stochastic processes under strong invariance. J. Comput. Appl. Math, 186:64-88, 2006 (with J. Steinebach). (Preprint)

 

Book Contributions, Book Reviews and Discussions

  • Ein Praxisbericht zur Kombination digitaler Elemente mit interaktiven Präsenzzeiten in der Mathematik-Lehre, Mitteilungen der DMV, 31(4):220-227, 2023 (with F. Aurzada, N. Stoffregen). Available here.
  • Editorial for the special issue on Time Series Analysis, CSDA, volume 181, 2023 (with K. Fokianos, H. Ombao). The final publication is available here.
  • Book review: Alexander G. Tartakovsky (2020): Sequential change detection and hypothesis - general non-i.i.d. stochastic models and asymptotically optimal rules, Statistical Papers, 2021. Article available at Springer.
  • Discussion of 'Detecting possibly frequent change-points: Wild Binary Segmentation 2 and steepest-drop model selection' by Fryzlewicz, Journal of the Korean Statistical Society, 2020 (with H. Cho). (Preprint on arXiv). Article available at Springer.
  • Special Issue with papers from the “3rd workshop on Goodness-of-fit and change-point problems”. Metrika, 81:587-588, 2018 (with N.Henze and S. G. Meintanis). The final publication is available at www.springerlink.com.
  • Detection of change points in discrete-valued time series (with J. Tadjuidje Kamgaing), 2016. In: Handbook of Discrete-Valued Time series. Eds. R. A. Davis, S. A. Holan, R. B. Lund, N. Ravishanker. (Preprint) The final publication is available at www.crcpress.com.
  • Comments on: Extensions of some classical methods in change point analysis by Horváth and Rice, Test, 23:270-275, 2014. The publication is available at www.springerlink.com.
  • Discussion on Multiscale change point inference  by Frick et al., J. Royal Statist. Soc. B, 76:495-580, 2014 (with J.A.D. Aston). The publication is available at Wiley.
  • Power Analysis for Functional Change Point Detection (with J.A.D. Aston), 2011. In: Recent Advances in Functional Data Analysis and Related Topics. Contributions to Statistics. Eds. F. Ferraty. Physica-Verlag HD. The final publication is available at www.springerlink.com.
  • Erfahrungsbericht in: Erfolg bei Studienarbeiten, Referaten und Prüfungen. Eds. S. Stock, P. Schneider, E. Peper und E. Molitor. Berlin: Springer 2009.

 

R Packages

  • mosum (with A. Meier, H. Cho), 2018, latest version 1.2.7, 2022, CRAN. Video-Talk. JSS-Paper.
  • beyondWhittle (with A. Meier, M. Edwards, R. Meyer, Y. Tang), 2017, latest version 1.2.0, 2023, CRAN.

 

Preprints on ArXiv

  • Scan statistics for the detection of anomalies in M-dependent random fields with applications to image data (with P. Klein, M. Meyer), 2023, preprint on arXiv, corresponding code on GitHub.
  • Variations of the depth based Liu-Singh two-sample test including functional spaces (with F. Gnettner, A. Nieto-Reyes), 2023, preprint on arXiv.
  • A nonparametrically corrected likelihood for Bayesian spectral analysis of multivariate time series (with Y. Liu, J. Lee, R. Meyer), 2023,  preprint on arXiv.
  • Bayesian nonparametric spectral analysis of locally stationary processes (with Y. Tang, J. Lee, R. Meyer), 2023, preprint on arXiv.

 

Conference Proceedings

  • Open problems in data segmentation algorithms. Oberwolfach Reports, 46:2670-2672, 2022.
  • Beyond time series stationarity: Smooth and abrupt changes. In Beyond Adaptation: Understanding distributional changes (Georg Krempl, Vera Hofer, Geoffrey Webb, and Eyke Hüllermeier), Report from Dagstuhl Seminar 20372, 2020 (appeared in 2021).
  • Generalizations of the Whittle likelihood for nonparametric spectral density estimation (with M. Edwards, A. Meier, R. Meyer). In Proceedings of the 32nd International Workshop on Statistical Modelling (Grzegorczyk, M., Ceoldo, D., eds), University of Groningen, Netherlands, Vol 1, 149-154, 2017.
  • Change-Points in High-Dimensional Settings (with J.A.D. Aston). Oberwolfach Reports, 48:2775-2778, 2013. (Preprint) (Report)
  • Fourier methods for sequential change point analysis in autoregressive models (with M. Hušková, S. Meintanis). Compstat 2010 conference proceedings, 8 pages, 2010
  • Bootstrapping Sequential Change-Point Tests (with M. Hušková). Proceedings of 2nd International Workshop in Sequential Methodologies, 6 pages, 2009.
  • Resampling Methods in Change-Point Analysis. Oberwolfach Reports, in 'Mini-Workshop: Time Series with Sudden Structural Changes', 5:557-586, 2008.
  • Resampling Methods for the Change Analysis of Dependent Data. Proceedings of the 15th European Young Statisticians Meeting, 5 pages, 2007.
  • Bootstrapping in the Frequency Domain of Time Series to Determine Critical Values for Change-Point Tests. Silesian Statistical Review, 4 (10), 132-134, 2005.

 

Qualification Theses

  • Resampling Methods for the Change Analysis of Dependent Data. Dissertation, Universität zu Köln, Juni 2006. (Referees: J. Steinebach (Köln), W. Wefelmeyer (Köln), M. Hušková (Prag)).
  • Permutationsprinzipien in der Changepoint-Analyse. Diplomarbeit, Philipps-Universität Marburg, Juli 2003. (Referees: J. Steinebach (Köln), V. Mammitzsch (Marburg)).

 

 

 

Letzte Änderung: 21.11.2018 - Ansprechpartner: Webmaster