english version
Nächster Vortrag im Stochastischen Kolloquium:
13.04.2018, 14:15, Dr. Paul Joubert (IMS-Alumni) (Berlin)

"Working as a data scientist in industry" (Abstract).
Dr. Yoav Zemel, EPF Lausanne, spends SNF Early Postdoc Mobility fellowship at IMS: The IMS welcomes Dr. Yoav Zemel, who is spending with us an 18-months research visit from February 1st, 2018 to July 31st, 2019. Dr. Zemel is funded by a Swiss National Science Foundation Early Postdoc Mobility fellowship for the project Uncertainty Quantification for Optimal Transport mentored by Prof. Axel Munk (more information is available here).

Arbeitsgruppe "Angewandte und Mathematische Statistik"

  • Röken, C., Schuppan, F., Proksch, K. and Schöneberg, S. (2018).
    Flaring of blazars from an analytical, time-dependent model for combined synchrotron and synchrotron self-Compton radiative losses of multiple ultrarelativistic electron populations. DOI:10.1051/0004-6361/201730622, Astronomy & Astrophysics. To appear.
  • Proksch, K., Werner, F., Munk, A. (2018).
    Multiscale scanning in inverse problems. The Annals of Statistics, arXiv:1611.04537. To appear.
  • Bissantz, K., Bissantz, N. and Proksch, K. (2017).
    Nonparametric detection of changes over time in image data from fluorescence microscopy of living cells. Submitted.
  • Chao, S.-K., Proksch, K., Dette, H. and Härdle, W. K. (2017).
    Confidence corridors for multivariate generalized quantile regression. Journal of Business & Economic Statistics, 35, 70-85.
  • Eckle, K., Bissantz, N., Dette, H., Proksch, K. Einecke, S. (2017).
    Multiscale inference for a multivariate density with applications to X-ray astronomy. DOI:10.1007/s10463-017-0605-1, Annals of the Institute of Statistical Mathematics. To appear.
  • Dunker, F., Eckle, K., Proksch, K. and Schmidt-Hieber, J. (2017).
    Tests for Qualitative Features in the Random Coefficients Model. arxiv.org/abs/1704.01066. Submitted.
  • Lucka, F., Proksch, K., Brune, C., Bissantz, N., Burger, M., Dette, H. and Wübbeling, F. (2017).
    Risk Estimators for Choosing Regularization Parameters in Ill-Posed Problems - Properties and Limitations. arxiv.org/abs/1701.04970. Submitted.
  • Einecke, S., Proksch, K., Bissantz, N., Clevermann, F. and Rhode, W. (2016).
    Uncertainty Limits on Solutions of Inverse Problems over Multiple Orders of Magnitude using Bootstrap Methods: An Astroparticle Physics Example. arXiv:1607.07226. Submitted.
  • Proksch, K. (2016).
    On confidence bands for multivariate nonparametric regression. Annals of the Institute of Statistical Mathematics, 68, 209-236.
  • Proksch, K., Bissantz, N. and Dette, H. (2015).
    Confidence bands for multivariate and time dependent inverse regression models. Bernoulli, 21, 144-175.
  • Bissantz, N., Holzmann, H. and Proksch, K. (2014).
    Confidence regions for images observed under the Radon transform. Journal of Multivariate Analysis, 128, 86-107.
  • Proksch, K. (2013).
    Asymptotic Normality of Kernel Estimators for Images Observed under the Radon Transform in Fan Beam Design. AIP Conf. Proc., 1558, 728-731 Submitted.
  • Proksch, K., Bissantz, N. and Dette, H. (2012).
    A note on asymptotic uniform confidence bands in a multivariate statistical deconvolution problem. AIP Conf. Proc., 1479, 438-441.
  • Bissantz, N., Dette, H. and Proksch, K. (2012).
    Model checks in inverse regression models with convolution-type operators Scandinavian Journal of Statistics., 39, 305-322.
  • Proksch, K., Bissantz, N. and Dette, H. (2011).
    On Bootstrapping L^2-Type Statistics in Inverse Regression Models with Convolution-Type Operators. AIP Conf. Proc., 1389, 414-418.