Fachbereich Mathematik 
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Dr. Tobias Niebuhr

E-Mail: tobias.niebuhr(at)uni-hamburg.de

Niebuhr, T., Junge, M. and Rosén, E. (2016): Pedestrian Injury Risk and the Effect of Age. Accident Analysis and Prevention, Vol. 86, pp. 121-128.

Kreiß, J.-P., Feng, G., Krampe, J., Meyer, M. and Niebuhr, T. (2015): Hochrechnung von GIDAS auf das Unfallgeschehen in Deutschland. FAT-Schriftenreihe 275, Verband der Automobilindustrie (VDA)/Forschungsvereinigung Automobiltechnik (FAT).

Kreiß, J.-P., Pastor, C., Dobberstein, J., Feng, G., Krampe, J., Meyer, M. and Niebuhr, T. (2015): Extrapolation of GIDAS accident data to Europe. Proceedings of The 24th International Technical Conference on the Enhanced Safety of Vehicles (ESV), paper no. 15-0372-O (Gothenburg, Sweden).

Niebuhr, T., Junge, M. and Achmus, S. (2015): Expanding pedestrian injury risk to the body region level: How to model passive safety systems in pedestrian injury risk functions. Traffic Injury Prevention, Vol. 16, No. 5, pp. 519-531.

Niebuhr, T. and Kreiß, J.-P. (2014): Asymptotics for autocovariances and integrated periodograms for linear processes observed at lower frequencies. The International Statistical Review, Vol. 82, No. 1, pp. 123-140. (DOI) 10.1111/insr.12019.

Brockwell, P. J., Kreiß, J.-P. and Niebuhr, T. (2014): Bootstrapping continuous-time autoregressive processes. The Annals of the Institute of Statistical Mathematics, Vol. 66, pp. 75-92. (DOI) 10.1007/s10463-013-0406-0.

Niebuhr, T., Junge, M. and Achmus, S. (2013): Pedestrian injury risk functions based on contour lines of equal injury severity using real world pedestrian/passenger-car accident data. The Annals of Advances in Automotive Medicine, Vol. 57, pp. 145-154.

Niebuhr, T., Kreiß, J.-P. and Achmus, S. (2013): GIDAS-aided quantification of the effectiveness of traffic safety measures in EU 27. Proceedings of The 23th International Technical Conference on the Enhanced Safety of Vehicles (ESV), paper no. 13-0167 (Seoul, Republic of Korea).

Niebuhr, T., Kreiß, J.-P. and Paparoditis, E. (2016): Some properties of the autoregressive-aided block bootstrap. Under Revision.

Niebuhr, T. and Junge, M. (2016): Detection of the toughest: Pedestrian injury risk as a smooth function of age. Under Revision.

Niebuhr, T. (2016): Irregularly observed time series - some asymptotics and the block bootstrap. Submitted.

Meyer, M. and Niebuhr, T. (2016): Testing for similiarity of discrete distributions. Submitted.

Niebuhr, T. (2016): A linear prediction algorithm for irregularly observed time series. Submitted.

Niebuhr, T. and Trabs, M. (2016): Adjusting estimators for marginal distributions in contingency tables. Submitted.

Hušková, M., Neumeyer, N., Niebuhr, T. and Selk, L. (2016): Specification testing in nonparametric AR-ARCH models.

Niebuhr, T. (2014): Bootstrap for continuous-time autoregressive moving average processes, Dissertation, TU Braunschweig.

Niebuhr, T. (2011): Statistik linearer Prozesse mit strukturellen Beobachtungslücken, Diplomarbeit, TU Braunschweig.

  Seitenanfang  Impress 2016-09-22, Tobias Niebuhr