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

  • Beyond Whittle: Nonparametric correction of a parametric likelihood with a focus on Bayesian time series analysis (with M.C. Edwards, A. Meier, R. Meyer). To appear in Bayesian Analysis, 2018+. (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.
  • 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 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.
  • 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.

 

 Conference Proceedings

  • 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)).

 

 

 

Lehrveranstaltungen

Wintersemester 2018/19

Einführung in die Wahrscheinlichkeitstheorie und Statistik: LSF Elearning

  • Einführung in die Wahrscheinlichkeitstheorie und Statistik (2 Übung Math): LSF
  • Einführung in die Wahrscheinlichkeitstheorie und Statistik (Übung LA): LSF

Oberseminar zur Stochastik: LSF

Explorative Datenanalyse und Wahrscheinlichkeit: LSF Elearning

Wintersemester 2017/18

Nichtparametrische Statistik: LSF

Oberseminar zur StochastikLSF

Statistische Modellierung und Datenanalyse LSF Elearning

  • Statistische Modellierung und Datenanalyse (9 Ü): LSF

Letzte Änderung: 15.05.2018 - Ansprechpartner:

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