Profil Dr. Stefanie Schwaar

Schwerpunkte/Kompetenzen

  • Analyse und Prognose von Zeitreihen
  • Nicht-lineare Regressionsmodelle 
  • Change-point Analyse
  • Machine Learning Methoden

 

Publikationen

  • Schwaar, S.:
    Asymptotics for change-point tests and change-point estimators.
    Dissertation, TU Kaiserslautern, (2017).
  • Dresvyanskiy, D.; Karaseva, T.; Mitrofanov, S.; Redenbach, C.; Makogin, V.; Spodarev, E.; Schwaar, S.:
    Application of Clustering Methods to Anomaly Detection in Fibrous Media.
    IOP Conference Series: Materials Science and Engineering, Vol. 537 (2), p.022001, (2019).
  • Blandfort, F.; Glock, C.; Sass, J.; Sefrin, S.; Schwaar, S.:
    A Parametric State Space Model for Time-Dependent Reliability Analysis.
    Accepted for 17th International Probabilistic Workshop (IPW2019), Edinburgh (2019).
  • Blandfort, F.; Glock, C.; Sass, J.; Sefrin, S.; Schwaar, S.:
    Subset Simulation Interpolation - A New Approach to Compute Effects of Model-Dynamics in Structural Reliability.
    Accepted for 29th European Safety and Reliability Conference (ESREL2019), Hannover (2019).
  • Schwaar, S.:
    Data-driven Change-Point Test and Estimator.
    Working Paper.