Institut für Mathematische Stochastik

Publikationen: Dannemann

  • Hartmann, A., Huckemann, S., Dannemann, J., Laitenberger, O., Geisler, C., Egner, A., Munk, A. (2016).
    Drift estimation in sparse sequential dynamic imaging: with application to nanoscale fluorescence microscopy. arXiv:1403.1389 Royal Statist. Society, Ser. , B78, 563–587.
  • Dannemann, J., Holzmann, H., Leister, A. (2014).
    Semiparametric hidden Markov models: Identification and estimation. WIREs Comp. Stat., 6, 418-425.
  • Dannemann, J. (2012).
    Semiparametric hidden Markov models. J. Comput. Graph. Statist., 21 (3), 677-692.
  • Dannemann, J., Munk, A. (2010).
    Discussion of "Maximum likelihood estimation of a multi-dimensional log-concave density" by Cule, Samworth and Stewart. J. Royal Statist. Society, Ser. B, 72, 593-595.
  • Dannemann. J., Holzmann, H. (2010).
    Testing for two components in a switching regression model. Comput. Statist. Data Anal., 64 (6), 1592-1604.
  • Dannemann, J. (2009, published 2010).
    Inference for Hidden Markov Models and related Models. Ph.D. thesis, University of Göttingen, Cuvillier Verlag , Göttingen.
  • Dannemann, J., Holzmann, H. (2008).
    Testing for two states in a hidden Markov model. Canad. J. Statist., 36 (4), 505-520 (Preprint).
  • Dannemann, J., Holzmann, H. (2008).
    Likelihood ratio testing for hidden Markov models under nonstandard conditions. Scand. J. Statist., 35 (2), 309-321 (Preprint).
  • Dannemann, J., Holzmann, H. (2008).
    The likelihood ratio test for hidden Markov models in two-sample problems. Computational Statistics & Data Analysis, 52, 1850-1859. (Preprint).
  • Dannemann, J. (2006).
    Maximum-Likelihood-Inferenz für Hidden Markow Modelle. Diploma thesis (unpublished), Georg-August-Universität Göttingen.