Theses
This page lists the current and finished theses at the Chair of Business and Social Statistics.
The campus of TU Dortmund University is located close to interstate junction Dortmund West, where the Sauerlandlinie A45 (Frankfurt-Dortmund) crosses the Ruhrschnellweg B1 / A40. The best interstate exit to take from A45 is “Dortmund-Eichlinghofen” (closer to South Campus), and from B1 / A40 “Dortmund-Dorstfeld” (closer to North Campus). Signs for the university are located at both exits. Also, there is a new exit before you pass over the B1-bridge leading into Dortmund.
For travelling to the Department of Statistics, convenient parking places can be found at Vogelpothsweg (Gates 21 / 24) or alternatively at the Otto-Hahn-Straße (Gates 28 / 30 / 35).
TU Dortmund University has its own train station (“Dortmund Universität”). From there, suburban trains (S-Bahn) leave for Dortmund main station (“Dortmund Hauptbahnhof”) and Düsseldorf main station via the “Düsseldorf Airport Train Station” (take S-Bahn number 1, which leaves every 15 or 30 minutes). The university is easily reached from Bochum, Essen, Mülheim an der Ruhr and Duisburg.
You can also take the bus or subway train from Dortmund city to the university: From Dortmund main station, you can take any train bound for the Station “Stadtgarten”, usually lines U41, U45, U 47 and U49. At “Stadtgarten” you switch trains and get on line U42 towards “Hombruch”. Look out for the Station “An der Palmweide”. From the bus stop just across the road, busses bound for TU Dortmund University leave every ten minutes (445, 447 and 462). Another option is to take the subway routes U41, U45, U47 and U49 from Dortmund main station to the stop “Dortmund Kampstraße”. From there, take U43 or U44 to the stop “Dortmund Wittener Straße”. Switch to bus line 447 and get off at “Dortmund Universität S”.
The H-Bahn is one of the hallmarks of TU Dortmund University. There are two stations on North Campus. One (“Dortmund Universität S”) is directly located at the suburban train stop, which connects the university directly with the city of Dortmund and the rest of the Ruhr Area. Also from this station, there are connections to the “Technologiepark” and (via South Campus) Eichlinghofen. The other station is located at the dining hall at North Campus and offers a direct connection to South Campus every five minutes.
The AirportExpress is a fast and convenient means of transport from Dortmund Airport (DTM) to Dortmund Central Station, taking you there in little more than 20 minutes. From Dortmund Central Station, you can continue to the university campus by interurban railway (S-Bahn). A larger range of international flight connections is offered at Düsseldorf Airport (DUS), which is about 60 kilometres away and can be directly reached by S-Bahn from the university station.
The facilities of TU Dortmund University are spread over two campuses, the larger Campus North and the smaller Campus South. Additionally, some areas of the university are located in the adjacent "Technologiepark".
Information for
Part of:
Department of StatisticsLars Wilmes | Graphon estimation | Master |
Jorge Alejandro Colin Paez | Comparing VAR-Based Forecasting Approaches in the Presence of Exogenous Shocks | Bachelor | 2023 |
Christopher Gerlach | Lasso and Fusion Penalization for periodic SVARs | Master | 2023 |
Priyanka Madiraju | Comparison of Diachronic Embeddings with Pre-trained Model Embeddings for Historical Texts | Master | 2023 |
Jannik Bloß | Comparison of Active Learning techniques for the benefit of data set generation in the field of text mining | Bachelor | 2023 |
Daniel Schürmann | An analysis of municipal vehicle data using classification methods and kernel density estimation [together with Diana Andrä, City of Dortmund, Dortmunder Statistik] | Master | 2023 |
Fabian Blunck | Prediction Intervals for Generalized Random Forests [together with Prof. Dr. Christoph Hanck, UDE, Award for outstanding thesis (Master Degree), Alumni-Verein Dortmunder Statistikerinnen und Statistiker] | Master | 2022 |
Cabrel Teguenme | AR-Sieve Bootstrap for the Random Forest and a simulation-based comparison with rangerts time series prediction [together with Prof. Dr. Markus Pauly] | Master | 2022 |
Aylin Girona | Bootstrapping für Propensity Score Matching | Bachelor | 2022 |
Yulia Shrub | Test data-based nowcasting of German GDP growth using newspaper data | Master | 2022 |
Dmitri Artjuch | Prediction in Modern Distribution Grids with Renewable Energy | Master | 2022 |
Kai-Robin Lange | Resampling strategies for unsupervised sentiment analysis using lexicon-based text embedding methods | Master | 2021 |
Daniel Dzikowski | Periodic structural VAR analysis | Master | 2021 |
Sven Ziegler | Prediction intervals for time series – a comparison of model-based and statistical learning techniques [together with Prof. Dr. Markus Pauly] | Master | 2021 |
Erik Weber | Parametrisierung einer Versicherungssparte für ein internes Risikomodell am Beispiel der kraftfahrt-Haftpflicht-Sparte des Continentale-Versicherungverbunds | Bachelor | 2021 |
Taha Abdolkarimi | Vorhersage von Aktienmärkten - ein Vergleich von Zeitreihen- und KünstlicheIntelligenz (KI)-Methoden [together with Prof. Dr. Markus Pauly] | Master | 2021 |
Axel Preis | Untersuchung von Bootstrap-Verfahren für Quantilsautoregressionen | Master | 2020 |
Maxime Faymonville | Bootstrap-based prediction for INAR processes | Master | 2020 |
Carolin Wäscher | Untersuchung schwacher Instrumente bei linearer Regression mit Instrumentalvariablen | Bachelor | 2020 |
Marlies Hafer | Vergleich von Bias-korrigierten Matching-Schätzern für den Average Treatment Effect | Bachelor | 2020 |
Raphael Meixner | Comparing penalisation approaches for high-dimensional ARCH processes | Master | 2020 |
Philipp Stockhaus | Vergleich der Zuverlässigkeit von Verfahren zur künstlichen Kontrollgruppenbildung mittels Krankenkassendaten | Master | 2020 |
Guy Merlin Tchamegni | Budget Stress Test, credit Risk Roll Rate Modelling and Projection | Master | 2019 |
Barbara Brune | On Subgraph Counts and Goodness-Of-Fit Testing for Stochastic Network Models [Preis für herausragende Abschlussarbeit (Abschlussart Master), Alumni-Verein Dortmunder Statistikerinnen und Statistiker] | Master | 2019 |
An Viet Nguyen | Modellierung und Prognose der Bundestagswahlen mit Hilfe von VAR-Modellen kompositioneller Daten | Bachelor | 2019 |
Fabian Erdmann | Mixed-Frequency Analyse makroökonomischer Daten mittels MIDAS | Bachelor | 2019 |
Daniel Dzikowski | Volatilitätsanalyse von Log-Renditen mittels multivariater GARCH | Bachelor | 2019 |
Johannes-Markus Yar | Bewertung von Modellrisiken durch Challengermodelle und –analysen - Conditional Inference Tree und Random Forest als Alternative zum klassischen Ratingverfahren | Master | 2018 |
Philipp Hallmeier | Spektraldichteschätzung mittels bootstrapbasiertem Thresholding der Fourierkoeffizienten | Master | 2018 |
Tobias Krabel | Residual Value Forecasting Using Tree-based Ensemble Methods: an Application to the Automobile Industry | Master | 2018 |
Shaikh Tanvir Hossain | Lasso & Vector Autoregressive Models - with Applications to Dynamic Stochastic Networks | Master | 2017 |
Marius Barckmann | On Germany's Intraday Power Market: Forecasting and Price Path Simulation | Master | 2017 |
Felix Prenzel | A comparison of different asymmetric GARCH models for financial data | Bachelor | 2017 |
Richard Grandpierre | Interest Revenue Forecasts for German Banks. A Dynamic Regression Tree Approach | Master | 2016 |
Julia Steinmetz | On the Network Topology of Variance Decompositions: Measuring the Connectedness of Financial Firms | Bachelor | 2016 |
Lukas Müller | Backtesting and Risk Measures | Bachelor | 2016 |
Florian Böser | Discrete Time Series Models and their Applications to Networks | Master | 2015 |
Florian Böser | Asymptotics of empirical autocovariances and autocorrelations in weakly linear models | Bachelor | 2013 |