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Dr. Jonas Krampe

Postdoctoral Researcher am Lehr­stuhl für Empirische Wirtschafts­forschung

Dr. Jonas Krampe

Jonas Krampe forscht und lehrt seit 2018 an der Universität Mannheim. Er promovierte 2018 in Mathematik (Dr. rer. nat.) am Institut für mathematische Stochastik an der TU Braunschweig. Seine Forschungs­schwerpunkte liegen in den Bereichen:

  • Hochdimensionale Statistik
  • Univariate und multivariate Zeitreihenanalyse
  • Bootstrap Methoden
  • Analyse von Unfalldaten
  • Forschung

    Theorie

    Preprints:

    • Krampe, J. and Margaritella, L. Dynamic Factor Models with Sparse VAR Idiosyncratic Components
    • Krampe, J. and Subba Rao, S. Inverse covariance operators of multivariate nonstationary time series

    Publications:

    • Krampe, J., Paparoditis, E., & Trenkler, C. (2022). Structural Inference in Sparse High-Dimensional Vector Autoregressions. Accepted in Journal of Econometrics.
    • Krampe, J., and Paparoditis, E. (2021) Sparsity Concepts and Estimation Procedures for High- Dimensional Vector Autoregressive Models. Journal of Time Series Analysis 42: 554-579.
    • Krampe, J., Kreiss, J.-P., and Paparoditis, E. (2021). Bootstrap Based Inference for Sparse High-Dimensional Time Series Model. Bernoulli 27.3: 1441-1466.
    • Krampe, J. and McMurry, T.L. (2021), Estimating Wold Matrices and Vector Moving Average Processes. Journal of Time Series Analysis, 42: 201–221
    • Krampe, J. (2019). Time Series Modeling on Dynamic Networks. Electronic Journal of Statistics, 13(2), 4945-4976.
    • Krampe, J., Kreiss, J.-P., and Paparoditis, E. (2018). Estimated Wold Representation and Spectral-density-driven Bootstrap for Time Series. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 80(4), 703-726.
    • 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.

    Anwendung

    Publications:

    • Krampe, J., and Junge, M. (2021) Deriving functional safety (ISO 26262) S-parameters for vulnerable road users from national crash data. Accident Analysis and Prevention, 150, 105884.
    • Krampe, J., and Junge, M. (2020). Injury Severity for Hazard and Risk Analyses: Calculation of ISO 26262 S-parameter Values from Real-world Crash Data. Accident Analysis and Prevention, 138, 105321.
    • Suppes, R., Ebrahimi, A., and Krampe, J. (2019). Optimising Casing Milling Rate Of Penetration (ROP) by Applying the Concept of Mechanical Specific Energy (MSE): A Justification of the Concept’s Applicability by Literature Review and a Pilot Study. Journal of Petroleum Science and Engineering, 180, 918-931.
    • Krampe, J., and Junge, M. (2019). Population-based Assessment of a Vehicle Fleet with Seat Belts Providing Lower Shoulder Belt Forces than Today. Traffic Injury Prevention, 20(3), 320-324.
    • Andricevic, N., Junge, M., and Krampe, J. (2018). Injury Risk Functions for Frontal Oblique Collisions. Traffic Injury Prevention, 19(5), 518-522.

Kontakt

Dr. Jonas Krampe

Postdoctoral Researcher am Lehr­stuhl für Empirische Wirtschafts­forschung
Universität Mannheim
Abteilung Volkswirtschafts­lehre
Lehr­stuhl für Empirische Wirtschafts­forschung

L 7, 3–5 – Raum 108
68161 Mannheim