Chair of Statistics - Final theses

Statistics | Final theses

Chair of Statistics - Final theses

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Student theses:

Author	Title	Supervisor
2025
Xianhong Wu	On Distance Graphical Models: A New Graphical Modelling Framework for Complex Data using Partial Distance Correlations	Matthias Eckardt
Jaeeun Shin	Spatial Uncertainty Quantification in DeepKriging: A Bayesian Approach	Matthias Eckardt
Ioannis Tsimalis	Deep GARCH: A New Tool for Forecasting Financial Asset Volatility	Matthias Eckardt
Lennart Mätzig	Graphical Modeling of Multivariate Spatio-Temporal Hawkes Processes on Linear Networks with Application to Crime Data	Matthias Eckardt
Dai Ruyu	Non-linear Mixture of Experts Models to Identify Heterogeneous Diet-Microbiome-Host Health Interactions	Sonja Greven
Mick Igel	Summary Characteristics for Network-Constrained Point Processes with Composition-valued Marks	Matthias Eckardt
Clemens Baldzuhn	Local Summary Characteristics for Marked Spatial Point Processes with Composition-valued Marks	Matthias Eckardt
Lukas Schimpf	Vector-valued Extension of Spatio-temporal Mark-weighted K Function: An Application on Wildfire Events in Australia	Matthias Eckardt
Simon Zimmermann	Causal Regularization for Marked Spatial Point Processes	Matthias Eckardt
Johannes Wagner	Principal Component Analysis for Sparsely Sampled-compositional Data with an Application to Marine Sediment Data	Matthias Eckardt
2024
Marie Bernière	Graphical Modeling of Spatially Distributed Extreme Events	Matthias Eckardt
Esther Weigmann	Exploring Hierarchical and Ordinal Deep Learning methods for Road Surface Classification	Xiangnan Zu
Laura Aschenberger	Analysis of Factors Influencing Real Estate Prices in Hawaii	Sigbert Klinke
Yury Svirydovich	Predicting Tooth Loss in Periodontitis Patients using Survival Analysis and Machine Learning Methods	Sonja Greven
Lea Runge	Conditional Density Regression for Individual-Level Longitudinal Data	Sonja Greven
Maarten Jung	Semi-structured Conditional Density Regression for Individual-level Data	Sonja Greven
Hila Zazai	Inwiefern beeinflusst das Ausmaß der Interaktion und der Unterstützungsleistungen zwischen Unternehmen und einer kaufmännischen Oberstufenzentrum die Zufriedenheit der Betriebe mit der Ausbildung und der Reduktion von vorzeitigen Ausbildungsabbrüchen?	Sigbert Klinke
Raphael Franke	Probabilistic Forecasting of PM10 Concentrations using Transformation Tree Models and Comparison with Existing Point Forecasts	Sonja Greven
Qingzi Huo	An Extension of the Generalized Covariance Measure for Conditional Independence Testing	Sonja Greven
Nils Cabos	Analyse der Wahrnehmung von Oberstufenzentren: Eine Untersuchung zu Merkmalen des Unterrichts und deren Zusammenhang mit dem Engagement und Lernzuwachs der Schüler	Sigbert Klinke
Maria Karimi	Evaluationsdaten von einem Gymnasium: Eine Analyse der Wahrnehmung von Lehrenden und Schüler:innen	Sigbert Klinke
2023
Chenyin Zhao	Comparison of Covariance Estimation Methods for Sparse Functional Data	Sonja Greven
Johannes Brandau	Invariant Feature Learning via Orthogonalization	Sonja Greven
Vincent Karpf	The Necessity of Complex Data: Object Importance by Removing for High-Dimensional Structured Objects	Sonja Greven
David Frohnau	Using Diffusion Models to Create Training Data for Image Classification Algorithms	Sonja Greven
Ana Karina Enriquez de los Rios	Functional Spatial Correlation Analysis on Crime Data of Mexico City	Sonja Greven
Maximilian Hildebrand	Blood Glucose Forecasting	Nadja Klein
Stanislav Slowinski	Der Einfluss der europäischen Struktur- und Investitionsfonds im Kontext des Problems der Heterogenität der Entwicklung in der Europäischen Union	Sonja Greven
Till Bethge	Bayesian Variable Selection for Ordinal Regression with an Application to Gene Expression Data	Nadja Klein
Johannes Feeser	On Estimating Causal Effects in Poisson-based Density Regression with an Application to the Retirement-Consumption Puzzle	Sonja Greven
Johannes Abele	Modelling Disease Severity using Semi- and Weakly Supervised Variational Autoencoders	Nadja Klein
Wei Ji Tan	Using the Horseshoe Prior for the Estimation of Non-linear Functions	Nadja Klein
Benedikt Lütke-Schwienhorst	Dropout Regularization in Generalized Linear Models Based on Double Exponential Families	Nadja Klein
2022
Till Baldenius	Analysing Heat and Experienced Racial Segregation Using Large-Scale Foot Traffic Data	Nadja Klein
Ákos Blaskovics	Application of Regression Trees on Compositional Data Using European Parliament Election Results	Sonja Greven
Julian Schneider	Extension of Treatment Effect Analysis to Dynamic Networks: An Application to PrEP in the context of HIV Transmission	Sonja Greven
Friedemann Brockmeyer	Summary Characteristics for Real-valued Marked Point Patterns on Linear Networks	Sonja Greven
Marco Simnacher	Extension of Generalized Additive Models to Graph-valued Data with Application to Covid-19 Impacts on European Air Transportation	Sonja Greven
Katja Weimer	Inference for Density-on-Scalar Regression in Bayes Hilbert Spaces	Sonja Greven
Henry Böddeker	Sizing Flags: Multi-Class Size Recommnedations for Fashion E-Commerce	Nadja Klein
Lucrece Mefowe Fokam	Correcting Underreporting in German Covid-19 Data	Sonja Greven
Felix Germaine	Interpretable Modelling of ICU Patients Remaining Length-of-Stay Distribution using Tabular Patient Data, Clinical Notes and Irregularly Spaced Clinical Measurement	Nadja Klein
2021
Bianca Neubert	Application of Hybrid Multivariate Functional Principal Component Analysis for the Analysis of Multivariate Spatial Point Process Summary Characteristics	Sonja Greven
Julius Freidank	Vergleich von Vorhersagemodellen zu Stornierungen von Hotelbuchungen	Sonja Greven
Jana Kleinemeier	Using Variational Inference to Estimate Structred Additive Distributional Regression Models	Nadja Klein
Anna Semenova	Reconstructing Multivariate Functional Data with Medical Applications	Sonja Greven
Manuel Pfeuffer	Elastic Full Procrustes Means for Sparse and Irregular Curves	Sonja Greven
Gesa Julia Kröger	Scalar-on-Composition Regression to evaluate the Impact of Class Competition on Educational achievement	Sonja Greven
Rodrigo Vazquez	Anomaly Data Quality Detection using Deep Autoencoders	Nadja Klein
Jost von Petersdorff-Campen	Copula Regression for Discrete Data – An Application to Covid-19	Nadja Klein
Yuliya Vandysheva	Die Modellierung der COVID-19-Fallzahlen in Abhängigkeit von Strukturdaten zu Wetter und Bevölkerung in Berlin	Nadja Klein
Chris Kolb	Application of Deep Distributional Regression to the Geospatial Distribution of Neglected Tropical Disease Vectors	Nadja Klein
Per Joachims	Uncertainty Quantification with Bayesian Neural Networks	Nadja Klein
Malgorzata Olesiewicz	Modelling of Missing not at Random Corporate Emissions Data for Sustainable Investment	Sonja Greven
Clara Hoffmann	Marginally Calibrated Posterior Densities for End-to-End Learning in Autonomous Driving	Nadja Klein
Michael Schimpke	Sentiment-Optimised Translation: An Approach for Multilingual Sealing of Pre-Trained Sentiment Classifiers	Nadja Klein
Jakub Kondek	Classification of Empathic and Non-Empathic Emails using Prototypical Networks	Nadja Klein
Silvia Ventoruzzo	On the Role of Weather in Predicting Online Sales of Different Product Categories	Nadja Klein
Safiul Alom	Uncertainty in Machine-Learning-based E-Mail Classification for Improved Customer Service	Nadja Klein
Lukas Mödl	The RODEO Approach for Nonparametric Density Estimation	Nadja Klein
2020
Anna Elisabeth Riha	Hyperpriorsensitivity of Bayesian Wrapped Gaussian Processes with an Application to Wind Data	Nadja Klein
Aaron Burgemeister	Benchmarking Different Machine Learning Methods Against Logistic Regression in Credit Scoring	Sonja Greven
Xiaoji Du	Analysis of a Restaurant Database of 31 European Cities	Sonja Greven
Jil Kollmus-Heege	Dynamic Prediction in Flexible Bayesian Additive Joint Models	Sonja Greven
Sisi Huang	An Image Classification Tool of Wikimedia Commons	Sonja Greven
Thomas Siskos	Career Recommendations using Supervised Latent Dirichlet Allocation	Sonja Greven
Kang Yang	Deep Generalised Additive Regression Models for Location, Scale and Shape	Nadja Klein
Paulina Kurowska	Bayesian Variable Selection Approach in Additive Quantile Regression	Nadja Klein
2019
Yinan Wu	Bayesian Adaptive Lasso for Zero Inflated Count Model and Overdispersion	Nadja Klein
Jerome Bau	Context-aware Sentence Generation from Keywords	Nadja Klein
Lukas Kemkes	Comparison and Combination of Extractive and Abstractive Techniques for Machine Text Summarization	Nadja Klein
Andrii Zakharov	Development of a Customer Insolvency Prediction Model following the Cross-Industry Standard Process for Data Mining (CRISP-DM)	Nadja Klein

Selected Theses:

Bachelor Theses

Regressionsmodelle und Hauptkomponentenanalyse für Billard-Bewegungstrajektorien (2019)
Classification of input devices using cursor trajectories (2017)
Funktions-auf-Skalar-Regression für Zellchipdaten (2015)
The Correlation Coefficient as a Measure of Similarity for Thermal Images in Medicine (2014)
Vergleich von Selektionskriterien für die Anzahl funktionaler Hauptkomponenten (2011)

Master Theses

A comparison of different approaches to the joint modelling of longitudinal and time-to-event outcomes (2019)
Multivariate functional regression models (2018)
Boosting flexible joint models for longitudinal and time-to-event data with medical applications
(2018)
Clustering räumlicher Kurven zur Identifikation von Laufmustern bei Hypermarathonläufern (2017)
Joint modelling of longitudinal biomarker measurements and time-to-event with an application in
patients with congestive heart failure (2017)
Multivariate Functional Principal Component Regression for Image Data with application to
Neuroimaging (2017)
Elastic Registration and Functional Principal Component Analysis of Curves in 1D and 2D (2017)
Boosting Generalized Additive Models for Location, Scale and Shape (GAMLSS) for Functional Data
(2016)
Joint modelling of multiple longitudinal islet autoantibody profiles and the onset of type 1 diabetes
(2015; Kooperation mit dem Helmholtz-Zentrum München)
Klassifikation von Spektren (2016)
Modellierung abhängiger/inhomogener Residuen in Regressionsmodellen für funktionale Responses
(2015)
A Comparison of Different Akaike Information Criteria in Linear Mixed Models (2014)
Elucidating multivariate effects of various ECG parameters on mortality and evaluation of potentially
underlying genetic components through genomewide association analyses (2014; Kooperation mit dem
Helmholtz-Zentrum München)
Novelty Detection Methods in High-Dimensional Spaces With An Application On Spectral Data (2014;
Kooperation mit Siemens)
Identifiability in Scalar-on-Functions Regression (2013)
Spatio-temporale Aspekte des Screening-Programms für Kolonkarzinome in Bayern (2011; mit Torsten
Hothorn)

Diploma Theses

Statistischer Performance-Vergleich für Klima-Chemie-Modelle (2012; mit Torsten Hothorn)
Conditional Akaike Information Criteria in Generalized Linear Mixed Models (2011; mit Thomas Kneib)

Humboldt-Universität zu Berlin - Statistics