40 citations · 162 across the 22 of their papers we have counts for
24 papers
The Politics of Language Choice: How the Russian-Ukrainian War Influences Ukrainians' Language Use on Twitter
Daniel Racek, Brittany I. Davidson, Paul W. Thurner +2
The use of language is innately political and often a vehicle of cultural identity as well as the basis for nation building. Here, we examine language choice and tweeting activity…
Sources of Uncertainty in Supervised Machine Learning -- A Statisticians' View
Cornelia Gruber, Patrick Oliver Schenk, Malte Schierholz +2
Supervised machine learning and predictive models have achieved an impressive standard today, enabling us to answer questions that were inconceivable a few years ago. Besides these…
COVID-19 and social media: Beyond polarization
Giacomo De Nicola, Victor H. Tuekam Mambou, Göran Kauermann
The COVID-19 pandemic brought upon a massive wave of disinformation, exacerbating polarization in the increasingly divided landscape of online discourse. In this context, popular s…
Actor Heterogeneity and Explained Variance in Network Models -- A Scalable Approach through Variational Approximations
Nadja Klein, Göran Kauermann
The analysis of network data has gained considerable interest in recent years. This also includes the analysis of large, high-dimensional networks with hundreds and thousands of no…
Modelling the large and dynamically growing bipartite network of German patents and inventors
Cornelius Fritz, Giacomo De Nicola, Sevag Kevork +2
We analyse the bipartite dynamic network of inventors and patents registered within the main area of electrical engineering in Germany to explore the driving forces behind innovati…
On assessing excess mortality in Germany during the COVID-19 pandemic
Giacomo De Nicola, Göran Kauermann, Michael Höhle
Coronavirus disease 2019 (COVID-19) is associated with a very high number of casualties in the general population. Assessing the exact magnitude of this number is a non-trivial pro…
Statistical modeling of on-street parking lot occupancy in smart cities
Marc Schneble, Göran Kauermann
Many studies suggest that searching for parking is associated with significant direct and indirect costs. Therefore, it is appealing to reduce the time which car drivers spend on f…
Matrix-free Penalized Spline Smoothing with Multiple Covariates
Julian Wagner, Göran Kauermann, Ralf Münnich
The paper motivates high dimensional smoothing with penalized splines and its numerical calculation in an efficient way. If smoothing is carried out over three or more covariates t…
The Role of Governmental Weapons Procurements in Forecasting Monthly Fatalities in Intrastate Conflicts: A Semiparametric Hierarchical Hurdle Model
Cornelius Fritz, Marius Mehrl, Paul W. Thurner +1
Accurate and interpretable forecasting models predicting spatially and temporally fine-grained changes in the numbers of intrastate conflict casualties are of crucial importance fo…
On the Interplay of Regional Mobility, Social Connectedness, and the Spread of COVID-19 in Germany
Cornelius Fritz, Göran Kauermann
Since the primary mode of respiratory virus transmission is person-to-person interaction, we are required to reconsider physical interaction patterns to mitigate the number of peop…
Mixture Models and Networks -- Overview of Stochastic Blockmodelling
Giacomo De Nicola, Benjamin Sischka, Göran Kauermann
Mixture models are probabilistic models aimed at uncovering and representing latent subgroups within a population. In the realm of network data analysis, the latent subgroups of no…
Nowcasting fatal COVID-19 infections on a regional level in Germany
Marc Schneble, Giacomo De Nicola, Göran Kauermann +1
We analyse the temporal and regional structure in mortality rates related to COVID-19 infections. We relate the fatality date of each deceased patient to the corresponding day of r…
Separable and Semiparametric Network-based Counting Processes applied to the International Combat Aircraft Trades
Cornelius Fritz, Paul W. Thurner, Göran Kauermann
We propose a novel tie-oriented model for longitudinal event network data. The generating mechanism is assumed to be a multivariate Poisson process that governs the onset and repet…
Intensity Estimation on Geometric Networks with Penalized Splines
Marc Schneble, Göran Kauermann
In the past decades, the growing amount of network data has lead to many novel statistical models. In this paper we consider so called geometric networks. Typical examples are road…
Estimation of Latent Network Flows in Bike-Sharing Systems
Marc Schneble, Göran Kauermann
Estimation of latent network flows is a common problem in statistical network analysis. The typical setting is that we know the margins of the network, i.e. in- and outdegrees, but…
A smooth dynamic network model for patent collaboration data
Verena Bauer, Dietmar Harhoff, Göran Kauermann
The development and application of models, which take the evolution of network dynamics into account are receiving increasing attention. We contribute to this field and focus on a…
Tempus Volat, Hora Fugit -- A Survey of Tie-Oriented Dynamic Network Models in Discrete and Continuous Time
Cornelius Fritz, Michael Lebacher, Göran Kauermann
Given the growing number of available tools for modeling dynamic networks, the choice of a suitable model becomes central. The goal of this survey is to provide an overview of tie-…
Regression-based Network Reconstruction with Nodal and Dyadic Covariates and Random Effects
Michael Lebacher, Göran Kauermann
Network (or matrix) reconstruction is a general problem which occurs if the margins of a matrix are given and the matrix entries need to be predicted. In this paper we show that th…
Censored Regression for Modelling International Small Arms Trading and its "Forensic" Use for Exploring Unreported Trades
Michael Lebacher, Paul W. Thurner, Göran Kauermann
In this paper we use a censored regression model to investigate data on the international trade of small arms and ammunition (SAA) provided by the Norwegian Initiative on Small Arm…
Exploring Dependence Structures in the International Arms Trade Network
Michael Lebacher, Göran Kauermann
In the paper we analyse dependence structures among international trade flows of major conventional weapons from 1952 to 2016. We employ a Network Disturbance Model commonly used i…
A Dynamic Separable Network Model with Actor Heterogeneity: An Application to Global Weapons Transfers
Michael Lebacher, Paul W. Thurner, Göran Kauermann
In this paper we propose to extend the separable temporal exponential random graph model (STERGM) to account for time-varying network- and actor-specific effects. Our application c…
Stable Exponential Random Graph Models with Non-parametric Components for Large Dense Networks
Stephanie Thiemichen, Göran Kauermann
Exponential Random Graph Models (ERGM) behave peculiar in large networks with thousand(s) of actors (nodes). Standard models containing two-star or triangle counts as statistics ar…
Bayesian Exponential Random Graph Models with Nodal Random Effects
Stephanie Thiemichen, Nial Friel, Alberto Caimo +1
We extend the well-known and widely used Exponential Random Graph Model (ERGM) by including nodal random effects to compensate for heterogeneity in the nodes of a network. The Baye…
Mixtures of g-Priors for Generalised Additive Model Selection with Penalised Splines
Daniel Sabanés Bové, Leonhard Held, Göran Kauermann
We propose an objective Bayesian approach to the selection of covariates and their penalised splines transformations in generalised additive models. Specification of a reasonable d…