Prof. Dr. Claudia Kirch

Prof. Dr. Claudia Kirch

Fakultät für Mathematik (FMA)
Institut für Mathematische Stochastik (IMST)
Universitätsplatz 2, 39106, Magdeburg, G18-422
Kurz-Vita
  • seit 2015 Professur für mathematische Stochastik, Otto-von-Guericke-Universität Magdeburg,  Fakultät für Mathematik, Institut für Mathematische Stochastik
  • 2014 Angebot einer Professur für Mathematische Statistik am Karlsruher Institut für Technologie (KIT)
  • 2009-2015 Juniorprofessur für Mathematische Statistik am Karlsruher Institut für Technologie (KIT)
  • 2008/9 Juniorprofessur für Angewandte Mathematische Statistik, Technische Universität Kaiserslautern
  • 2006-2008 Post-Doktorandin am GRK 753 Mathematik und Praxis. Modellierung, Optimierung, Prognose und Steuerung von technischen, ökonomischen und medizinischen Systemen, Technische Universität Kaiserslautern
  • 2006 Dissertation, Institut für Mathematik, Universität zu Köln
  • 2003-2006 Wissenschaftliche Mitarbeiterin, Universität zu Köln
  • 2003 Diplom in Mathematik, Philipps-Universität Marburg

 

Meine Google-Scholar-Autorenseite

ResearcherID

Projekte
Publikationen

Publications in Refereed Journals

  • 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.
  • 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. 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. 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 and Discussions

  • 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. The publication is available at Wiley.
  • Erfahrungsbericht in: Erfolg bei Studienarbeiten, Referaten und Prüfungen. Eds. S. Stock, P. Schneider, E. Peper und E. Molitor. Berlin: Springer 2009.

 

 Conference Proceedings

  • Change-Points in High-Dimensional Settings (with J. Aston). Oberwolfach Reports, 48:2775-2778, 2013. (Preprint) (Report)
  • Power analysis for functional change point detection (with J. Aston). Recent advances in functional data analysis and related topics, selected papers from the 2nd International Workshop on Functional and Operatorial Statistics, 23–26, Contrib. Statist., Physica-Verlag/Springer, Heidelberg, 2011.
  • 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.

 

Preprints

  • Beyond Whittle: Nonparametric correction of a parametric likelihood with a focus on Bayesian time series analysis (with M.C. Edwards, A. Meier, R. Meyer). (Preprint on arXiv)

 

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)).

 

 

 

Lehrveranstaltungen

Wintersemester 2017/18

Nichtparametrische Statistik: LSF

Oberseminar zur Stochastik: LSF

Statistische Modellierung und Datenanalyse: LSF Elearning

  • Statistische Modellierung und Datenanalyse (9 Ü): LSF

Letzte Änderung: 15.05.2018 - Ansprechpartner:

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