Publications

Publications

ORCID: 0000-0001-6446-4558

Monographs:

  • Andersen, T.G., Davis, R.A., Kreiss, J.-P. and Mikosch, T. (Eds.) (2009). Handbook of Financial Time Series. Springer-Verlag, New York.
  • Kreiss, J.-P. und Neuhaus, G. (2006). Einführung in die Zeitreihenanalyse. Springer-Verlag.

Articles and Preprints:

  • Kreiss, J.-P., Leucht, A. and Paparoditis, E. (2024). Gaussian Approximation for Lag-Window Estimators and the Construction of Confidence Bands for the Spectral Density. Submitted.
  • Rademacher, D., Kreiss, J.-P. and Paparoditis, E. (2024): Asymptotic Normality of Spectral Means of Hilbert Space Valued Random Processes. Stochastic Processes and their Applications, 173, 104357.
  • Kreiss, J.-P. and Paparoditis, E. (2023): Bootstrapping Whittle Estimators. Biometrika, 110, 499-518.
  • Schmidt-Melchiors, T., Kreiss, J.-P. and Braumann, A. (2022): Adverse effects of vaccinations against the Corona-virus SARS-CoV-2: insights and hindsights from a statistical perspective.
  • Kreiss, J.-P. and Schmidt-Melchiors, T. (2021): Nebenwirkungen von Impftstoffen gegen das Corona-Virus SARS-CoV-2: Eine statistische Analyse.
  • Braumann, A., Krampe, J., Kreiss, J.-P. and Paparoditis, E. (2021): Estimation of the Distribution of the Reproduction Number: The Case of the COVID19-Pandemic.
  • Braumann, A., Kreiss, J.-P. and Meyer, M. (2021): Simultaneous Inference for Autocovariances based on Autoregressive Sieve Bootstrap. Journal of Time Series Analysis, 42, 534-553.
  • Krampe, J., Kreiss, J.-P. and Paparoditis, E. (2021): Bootstrap based inference for sparse high-dimensional time series models. Bernoulli, 27, 1441-1466.
  • Meyer, M., Paparaoditis, E. and Kreiss, J.-P. (2020): Extending the validity of frequency domain bootstrap methods to general stationary processes. The Annals of Statistics, 48, 2404-2427.
  • Krampe, J., Kreiss, J.-P. and Paparoditis, E. (2018): Estimated Wold representation and spectral-density-driven bootstrap for time series. Journal of the Roy. Statist. Soc. Ser. B, 80, 703-726.
  • Niebuhr, T., Kreiss, J.-P. and Paparoditis, E. (2017): Some properties of the autoregressive-aided block bootstrap. Electronic Journal of Statistics, 11, 725-751.
  • Meyer, M., Jentsch, C. and Kreiss, J.-P. (2017). Baxter's inequality and sieve bootstrap for random fields. Bernoulli, 23, 2988-3020.
  • Meister, A. and Kreiss, J.-P. (2016): Statistical Inference for Nonparametric of GARCH Models. Stochastic Processes and Their Applications, 126, 3009-3040.
  • Löwe, T., Förster, E.-C., Albuquerque, G., Kreiss, J.-P. and Magnor, M. (2016). Visual Analytics for Development and Evaluation of Order Selection Criteria for Autoregressive Processes. IEEE Transactions on Visualization & Computer Graphics (TVCG), 22, 151-159.
  • Kreiss, J.-P. (2016). Discussion to a paper on Bootstrap prediction intervals for linear, nonlinear and nonparametric autoregressions by L. Pan and D.N. Politis. J. Statist. Plan. Inference, 177, 28-30.
  • Krampe, J., Kreiss, J.-P. and Paparoditis, E. (2015). Hybrid wild bootstrap for nonparametric trend estimation in locally stationary time series. Statistics and Probability Letters, 101, 54-63.
  • Kreiss, J.-P., Pastor, C., Dobberstein, J., Feng, G., Krampe, J., Meyer, M. and Niebuhr, T. (2015). Extrapolation of GIDAS accident data to Europe. 24th International Technical Conference on the Enhanced Safety of Vehicles (ESV), paper no. 15-0372 (Gothenburg, Sweden).
  • Leucht, A., Neumann, M.H. and Kreiss, J.-P. (2015). A model specification test for GARCH(1,1) processes. Scandinavian Journal of Statistics, 42, 1167-1193.
  • Meyer, M. and Kreiss, J.-P. (2015): On the Vector Autoregressive Sieve Bootstrap. Journal of Time Series Analysis, 36, 377-397.
  • Kreiss, J.-P., Feng, G., Krampe, J., Meyer, M. and Niebuhr, T. (2014). Methoden zur Hochrechnung von GIDAS-Daten auf Europa. Bericht der Bundesanstalt für Straßenwesen, to appear.
  • Kreiss, J.-P., Feng, G., Krampe, J., Meyer, M. and Niebuhr, T. (2014). Methoden zur Hochrechnung von GIDAS-Daten auf Deutschland. Bericht der Forschungsvereinigung Automobiltechnik (FAT) e.V., FAT 275.
  • Feng, G. and Kreiss, J.-P. (2014): Bootstrapping Realized Bipower Variation. In: Topics in Nonparametric Statistics, Springer Proceedings in Mathematics & Statistics, Vol. 74, 85-93.
  • Fink, T. and Kreiss, J.-P. (2014). Simultaneous Bootstrap for all three Parameters in Random Coefficient Autoregressive Models. J. of the Korean Statistical Society, 43, 425-438.
  • Brockwell, P.J., Kreiss, J.-P. and Niebuhr, T. (2014): Bootstrapping continuous-time autoregressive processes. Annals of the Institute of Statistical Mathematics, 66, 75-92.
  • Kreiss, J.-P. and Paparoditis, E. (2014): Bootstrapping Locally Stationary Time Series. Journal of the Roy. Statist. Soc. Ser. B, 77, 267-290.
  • Niebuhr, T. and Kreiss, J.-P. (2014). Asymptotics for Autocovariances and Integrated Periodograms for Linear Processes Observed at Lower Frequencies. International Statistical Review, 82, 123-140.
  • Fink, T. and Kreiss, J.-P. (2013). Bootstrap for Random Coefficient Autoregressive Models. Journal of Time Series Analysis, 34, 646-667.
  • Jentsch, C., Kreiss, J.-P., Mantalos, P. and Paparoditis, E. (2012): Hybrid Bootstrap Aided Unit Root Testing. Computational Statistics, 27, 779-797.
  • Kreiss, J.-P. and Paparoditis, E. (2012): The Hybrid Wild Bootstrap for Time Series. J. American Statistical Association, 107, 1073-1084.
  • Kreiss, J.-P. and Lahiri, S.N. (2012): Bootstrap Methods for Time Series. In: Handbook of Statistics, Vol 30: Time Series-Methods and Applications, Elsevier-North Holland, 3-26.
  • Kreiss, J.-P. and Paparoditis, E. (2011): Bootstrap for Dependent Data: A Review (with Discussion). J. Korean Statistical Society, 40, 357-395.
  • Kreiss, J.-P., Paparoditis, E. and Politis, D.N. (2011): The Range of Vailidity of the Autoregressive Sieve Bootstrap. The Annals of Statistics, 39, 2103-2130.
  • Kreiss, J.-P. and Zangmeister, T. (2011): New Findings on the Usage of Logistic Regression in Accident Data Analysis. 22th International Technical Conference on the Enhanced Safety of Vehicles (ESV), paper no. 11-0192 (Washington D.C., USA).
  • Kreiss, J.-P., Stanzel, M. and Zobel, R. (2011): On the Use of Real-World Accident Data for Assessing the Effectiveness of Automotive Safety Features: Methodology, Timeline and Reliability. 22th International Technical Conference on the Enhanced Safety of Vehicles (ESV), paper no. 11-0054 (Washington D.C., USA).
  • Kreiss, J.-P. and Zangmeister, T. (2011): Quantification of the effectiveness of a safety function in passenger vehicles on the basis of real - world accidents. Fraunhofer ITWM, Bericht Nr. 203 (2011).
  • Jentsch, C. and Kreiss, J.-P. (2010): The Multiple Hybrid Bootstrap - Resampling Multivariate Linear Processes. J. Mult. Analysis, 101, 2320-2345.
  • Kreiss, J.-P. (2009): Fahrerassistenzsysteme. Der Kfz-Sachverständige, Jg. 4 Heft 5, 21-24.
  • Page, Y., Cuny, S., Zangmeister, T., Kreiss, J.-P. and Hermitte, T. (2009): The Evaluation of the Safety Benefits of Combined Passive and On-Board Active Safety Applications. Proceedings of the 53rd Annual Conference of the Association for the Advancement of Automotive Medicine (AAAM) (Baltimore, USA).
  • Zangmeister, T., Kreiss, J.-P., Page, Y. and Cuny, S. (2009): Evaluation of the Safety Benefits of Passive and/or On-Board Active Safety Applications with Mass Accident Data-Bases. 21th International Technical Conference on the Enhanced Safety of Vehicles (ESV) (Stuttgart, Germany).
  • Franke, J., Kreiss, J.-P. and Mammen, E. (2009): Nonparametric modelling of financial time series. In: Andersen, T.G., Davis, R.A., Kreiss, J.-P. and Mikosch, T. (Eds.): Handbook of Financial Time Series. Springer-Verlag, New York, 927-952.
  • Kreiss, J.-P., Neumann, M.H. and Yao, Q. (2008). Bootstrap tests for simple structures in nonparametric time series regression. Statistics And Its Interface, 1, 367-380.
  • Kreiss, J.-P. and Dürkes, A. (2007). Nonparametric modelling and estimation of stochastic volatility. Working paper, Technische Universität Braunschweig.
  • Kreiss, J.-P., Schüler, L. and Zangmeister, T. (2007). Simultaneous Evaluation of Multiple Safety Functions in Passenger Vehicles. 20th International Technical Conference on the Enhanced Safety of Vehicles (ESV) (Lyon, France).
  • Franke, J., Kreiss, J.-P. und Moser, M. (2006). Bootstrap Order Selection for Autoregressive Processes. Statistics and Decisions, 24, 305-325.
  • Hidalgo, J. and Kreiss, J.-P. (2005). Bootstrap specification tests for linear covariance stationary processes. Journal of Econometrics, 133, 807-839.
  • Kreiss, J.-P., Langwieder, K. and Schüler, L. (2005). The effectiveness of primary safety features in passenger cars in Germany. 19th International Technical Conference on the Enhanced Safety of Vehicles (ESV) (Washington D.C., USA).
  • Kreiss, J.-P., Zobel, R. and Busch, S. (2003). Essential components of a statistically valid crashworthiness rating. 18th International Technical Conference on the Enhanced Safety of Vehicles (ESV) (Nagoya, Japan).
  • Kreiss, J.-P. and Paparoditis, E. (2003). Autoregressive aided periodogram bootstrap. Annals of Statistics, 31, 1923-1955.
  • Härdle, W., Horowitz, J. and Kreiss, J.-P. (2003). Bootstrap for Time Series. International Statistical Review, 71, 435-459.
  • Franke, J., Härdle, W. and Kreiss, J.-P. (2003). Nonparametric estimation in a stochastic volatility model. Recent Advances and Trends in Nonparametric Statistics (Akritas, M.G. and Politis, D.N. (Eds.)), 303-313.
  • Franke, J., Kreiss, J.-P., Mammen, E. and Neumann, M. H. (2002). Properties of the nonparametric autoregressive bootstrap. Journal of Time Series Analysis, 23, 555-585.
  • Franke, J., Kreiss, J.-P., Mammen, E. (2002). Bootstrap of kernel smoothing in nonlinear time series. Bernoulli, 8, 1-37.
  • Busch, S., Kreiss, J.-P. and Zobel, R. (2002). Determination of risk factors of accident causation. Proceedings of the conference on Vehicle Safety 2002 of the Institution of Mechanical Engineers (I MECH E)}, London.
  • Kreiss, J.-P. (2000). Nonparametric Estimation and Bootstrap for Financial Time Series. In: Statistics and Finance: An Interface (W.S. Chan, W.K. Li and H. Tong (Eds.)). Imperial College Press, London, 2000.
  • Kreiss, J.-P. und Neumann, M.H. (1999). Bootstrap Tests for Parametric Volatility Structure in Nonparametric Autoregression. In: Prob. Theory and Math. Stat. (B. Grigelionis et al. (Eds.)), 1999, 393-404.
  • Neumann, M.H. und Kreiss, J.-P. (1998). Regression-Type Inference in Nonparametric Autoregression. The Annals of Statistics, Vol. 26, No. 4, 1998, 1570-1613.
  • Kreiss, J.-P. (1997). Asymptotical Properties of Residual Bootstrap for Autoregression. Technical Report, TU Braunschweig. pdf
  • Kreiss, J.-P. und Neumann, M.H. (1996). Bootstrap Confidence Bands for the Autoregression Function. Discussion Paper No. 75, 1996, SFB 373.
  • Heimann, G. und Kreiss, J.-P. (1996). Bootstrapping General First Order Autoregression. Statistics and Probability Letters, Vol. 30, 1996, 87-98.
  • Kreiss, J.-P. (1992). Bootstrap Procedures for AR(∞)-Processes. Lecture Notes in Economics and Mathematical Systems No. 376 (Proc. Bootstrapping and Related Techniques, Trier), 1992, 107-113.
  • Franke, J. und Kreiss, J.-P. (1992). Bootstrapping Stationary Autoregressive Moving-Average Models. Journal of Time Series Analysis, Vol. 13, 1992, 297-317.
  • Kreiss, J.-P. (1991). Estimation of the Distribution Function of Noise in Stationary Linear Processes. Metrika, Vol. 38, 1991, 285-297.
  • Kreiss, J.-P. (1990). Local Asymptotic Normality for Autoregression with Infinite Order. Journal of Statistical Planning and Inference, Vol. 26, 1990, 185-219.
  • Kreiss, J.-P. (1990). Testing Linear Hypotheses in Autoregressions. The Annals of Statistics, Vol. 18, 1990, 1470-1482.
  • Kreiss, J.-P. (1988). Asymptotic Statistical Inference for a Class of Stochastic Processes. Habilitationsschrift, Fachbereich Mathematik der Universität Hamburg.
  • Kreiss, J.-P. (1988). On Stochastic Estimation. The Annals of the Institute of Statistical Mathematics, Vol. 40, 1988, 507-520.
  • Kreiss, J.-P. (1987). On adaptive Estimation in Stationary ARMA Processes. The Annals of Statistics, Vol. 15, 1987, 112-133.
  • Kreiss, J.-P. (1987). On adaptive Estimation in Autoregressive Models when there are Nuisance Functions. Statistics and Decisions, Vol. 5, 1987, 59-76.
  • Kreiss, J.-P. (1986). Repeated Significance Tests for Stationary ARMA Processes. Sequential Analysis, Vol. 5, 1986, 103-126.
  • Kreiss, J.-P. (1985). A Note on M-Estimation in Stationary ARMA Processes. Statistics and Decisions, Vol. 3, 1985, 317-336.
  • Neuhaus. G. und Kreiss, J.-P. (1985). Einführung in die Zeitreihenanalyse. Skripten zur Mathematischen Statistik Nr. 10 der Gesellschaft zur Förderung der Mathematischen Statistik, Münster.
  • Kreiss, J.-P. (1984). Adaptive Estimation and Testing in ARMA-Models (the multivariate case). Preprint No. 84-5, Institut für Mathematische Stochastik der Universität Hamburg.
  • Kreiss, J.-P. (1984). Existenz und Konstruktion von adaptiven Schätzfolgen in ARMA(p,q)-Modellen. Dissertation, Fachbereich Mathematik der Universität Hamburg.