english version
Nächster Vortrag im Stochastischen Kolloquium:
25.10.2017, 11:15, Dr. Vlada Limic (Université Paris Sud 11)

"Title: t.b.a.".
Statistics Meets Friends: The workshop "Statistics Meets Friends - from biophysics to inverse problems and back -" takes place in Göttingen from November 29th to December 1st, 2017.

Arbeitsgruppe "Angewandte und Mathematische Statistik"
Publikationen: Gesamtliste

SFB803 - Z2

  • Pein, F., Hotz, T., Sieling, H., Aspelmeier, T. (2017).
    stepR - an R package for change-point inference.
  • Pein, F., Hotz, T., Tecuapetla-Gómez, I., Aspelmeier, T. (2017).
    clampSeg - an R package for idealisation of patch clamp recordings.
  • Pein, F., Tecuapetla-Gómez, I., Schütte, O. M., Steinem, C., Munk, A. (2017).
    Fully-Automatic Multiresolution Idealization for Filtered Ion Channel Recordings: Flickering Event Detection arxiv.org 1706.03671. Submitted.
  • Gawthrop, P., Siekmann, I., Kameneva, T., Saha, S., Ibbotson, M. R. and Crampin, E. J. (2017).
    Bond Graph Modelling of Chemoelectrical Energy Transduction. Submitted.
  • Behr, M., Holmes, C., Munk, A. (2017).
    Multiscale blind source separation. The Annals of Statistics, arXiv:1608.07173. To appear.
  • Behr, M., Munk, A. (2017).
    Identifiability for blind source separation of multiple finite alphabet linear mixtures. arxiv.org 1505.05272 , IEEE Trans. Inf. Theory. To appear.
  • Pein, F., Sieling, H., Munk, A. (2017).
    Heterogeneuous change point inference (R package: HSMUCE). arxiv.org 1505.04898, Journ. Royal. Statist. Soc. Ser. B, 79, 1207–1227.
  • Siekmann, I., Fackrell, M., Taylor, P. and Crampin, E. J. (2016).
    Modelling modal gating in ion channels with hierarchical Markov models. Proceedings of the Royal Society of London A, 472, 20160122.
  • Siekmann, I. and Malchow, H. (2016).
    Fighting Enemies and Noise: Competition of Residents and Invaders in a Stochastically Fluctuating Environment. Mathematical Modelling of Natural Phenomena (MMNP), 11(5), 120-140.
  • Hafi, N., Grunwald, M., van den Heuvel, L. S., Aspelmeier, T., Chen, J.-H., Zagrebelsky, M., Schuette, O. M., Steinem, C., Korte, M., Munk, A., Walla, J. P. (2016).
    Corrigendum: Fluorescence nanoscopy by polarization modulation and polarization angle narrowing. Nature Methods, 13, 101.
  • Hafi, N., Grunwald, M., van den Heuvel, l.S., Aspelmeier, T., Steinem, C., Korte, M., Munk, A., Walla, J.P. (2016).
    Reply to "Polarization modulation adds little additional information to super-resolution fluorescence microscopy" Nature Methods, 13, 8-9.
  • Tecuapetla-Gómez, I., Munk, A. (2016).
    Autocovariance estimation in regression with a discontinuous signal and m-dependent errors: A difference-based approach (R package: dbacf). Scandinavian Journal of Statistics (arxiv.org 1507.02485v4). Accepted.
  • Li, H., Munk, A., Sieling, H. (2016).
    FDR-control in multiscale change-point segmentation. Electron. J. Statist., 10(1), 918-959.
  • Pein, F. (2015).
    HSMUCE - an R package for change-point inference for heterogeneous data.
  • Futschik, A., Hotz, T., Munk, A., Sieling, H. (2014).
    Multiscale DNA partitioning: statistical evidence for segments. Bioinformatics, doi: 10.1093/bioinformatics/btu180 (Preprint).
  • Frick, S., Hohage, T., Munk, A. (2014).
    Asymptotic laws for change point estimation in inverse regression. Statistica Sinica, 24, 555-575 (Preprint).
  • Frick, K., Munk, A., Sieling, H. (2014).
    Multiscale Change-Point Inference (software "stepR" for multiscale change point analysis "SMUCE") With discussion and rejoinder by the authors. Journ. Royal Statist. Society, Ser. B, , 76, 495-580. arXiv:1301.7212 long version with full proofs.
  • Hotz,T., Schütte, O., Sieling, H., Polupanow, T., Diederichsen, U., Steinem, C., Munk, A. (2013).
    Idealizing ion channel recordings by jump segmentation and statistical multiresolution analysis IEEE Trans. on NanoBioScience, 12, 376-386. (Preprint).
  • Hotz, T., Huckemann, S., Le, H., Marron, J. S., Mattingly, J. C., Miller, E., Nolen, J., Owen, M., Patrangenaru, V., Skwerer, S. (2013).
    Sticky central limit theorems on open books. Annals of Applied Probability, 23(6) 2238-2258 , 1202.4267 [math.PR] [math.MG] [math.ST].
  • Krivobokova, T., Briones, R., Hub, J., Munk, A., de Groot, B. (2012).
    Partial least squares functional mode analysis: application to membrane proteins AQP1, Aqy1 and CLC-ec1 Biophysical Journal, 103, 786-796.
  • Frick, K., Marnitz, P., Munk, A. (2012).
    Statistical Multiresolution Dantzig Estimation in Imaging: Fundamental Concepts and Algorithmic Framework Electron. J. Stat., 6, 231-268.
  • Hotz, T., Gottschlich, C., Lorenz, R., Bernhardt, S., Hantschel, M., Munk, A. (2011).
    Statistical Analyses of Fingerprint Growth. BIOSIG 2011 - Proceedings - International Conference of the Biometrics Special Interest Group, 08.-09. September 2011 in Darmstadt, Germany. Lecture Notes in Informatics, P-191, 11-20.
  • Gottschlich, C., Hotz, T., Lorenz, R., Bernhardt, S., Hantschel, M., Munk, A. (2011).
    Modeling the Growth of Fingerprints Improves Matching for Adolescents IEEE Transactions on Information Forensics and Security, 6(3), 1165-1169.
  • Huckemann, S., Hotz, T., Munk, A. (2010).
    Intrinsic MANOVA for Riemannian Manifolds with an Application to Kendalls Spaces of Planar Shapes. IEEE Trans. Patt. Anal. Mach. Intell., 32 (4), 593-603, "Spotlight Paper" for this issue with its "Special Section on Shape Analysis and its Applications in Image Understanding", freely available until 18 March 2010 (Preprint).