activity
20162023
most citedSources of Uncertainty in Supervised Machine Learning -- A Statisticians' View

18 citations · 23 across the 10 of their papers we have counts for

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Showing 2020 · stat.APShow all

5 papers · 2 filters

stat.AP2020

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…

stat.AP2020

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…

stat.AP2020

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…

stat.AP2020

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…

stat.AP2020

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…