Informationen zu Masterarbeiten

Voraussetzungen:

Um mit einer Masterarbeit am Lehrstuhl anfangen zu können, müssen Sie mindestens drei der folgenden Module bestanden haben

  • Applied Regression [MA4401]
  • Computational Statistics [MA3402]
  • Generalized Linear Models [MA3403]
  • Quantitative Risk Management [MA5415]
  • Stochastic Analysis [MA4405]
  • Time Series Analysis [MA3411]

Zusätzlich müssen Sie ein Masterseminar am Lehrstuhl (oder eine fachlich äquivalente Leistung) erfolgreich bestanden haben.

 

 

Laufende Arbeiten

  • Hochsprung, Tom: Learning sparse Gaussian graphical models with few covariance queries (Mathias Drton, Carlos Amendola Ceron)
  • Bulté, Matthieu: Higher-order statistics for high-dimensional problems with applications to graphical models (Mathias Drton)
  • Haffner, Stefan: Two likelihood-ratio based approaches for interval estimation of causal effects in linear structural equation models (Mathias Drton)
  • Mareis, Leopold: Vine copula based quantile regression including discrete components (Claudia Czado, Marija Tepegjozova)
  • Dreier, Lukus: Identifiability of Cyclic Structural Equation Models with Gaussian Homoscedastic Error Terms (Mathias Drton, Miguel de Benito Delgado)
  • Scharl, Sebastian: D-vine regression based Bayesian network analysis of the Sachs data (Claudia Czado)
  • Allwright, Emma: Development of an enhanced additive logistic regression model for European thunderstorms and their associated hazards (Claudia Czado)
  • Martonak, Michal: Bayesian modelling of insurance risks with deep learning (Mathias Drton)
  • Kollosche, Susan: Statistical analysis of energy appliance data (Claudia Czado, Alexander Kreuzer)

Nützliches