10 citations · 15 across the 10 of their papers we have counts for
10 papers
Probabilistic Deep Learning for Drought Forecasting: Role of Internal Climate Variability
Henri Funk, Cornelia Gruber, Göran Kauermann +2
Predicting drought risk is essential for anticipating impacts on water resources, agriculture, ecosystems, and climate adaptation planning. Yet drought forecasts remain uncertain b…
Capturing Aleatoric Uncertainty in Climate Models
Cornelia Gruber, Henri Funk, Magdalena Mittermeier +2
Internal climate variability arises from the climate system's inherently chaotic dynamics. Quantifying it is essential for climate science, as it enables risk-based decision-making…
Deriving Duration Time from Occupancy Data -- A case study in the length of stay in Intensive Care Units for COVID-19 patients
Martje Rave, Göran Kauermann
This paper focuses on drawing information on underlying processes, which are not directly observed in the data. In particular, we work with data in which only the total count of un…
The Skellam Distribution revisited -Estimating the unobserved incoming and outgoing ICU COVID-19 patients on a regional level in Germany
Martje Rave, Göran Kauermann
With the beginning of the COVID-19 pandemic, we became aware of the need for comprehensive data collection and its provision to scientists and experts for proper data analyses. In…
Estimating excess mortality in high-income countries during the COVID-19 pandemic
Giacomo De Nicola, Göran Kauermann
Quantifying the number of deaths caused by the COVID-19 crisis has been an ongoing challenge for scientists, and no golden standard to do so has yet been established. We propose a…
Dependence matters: Statistical models to identify the drivers of tie formation in economic networks
Giacomo De Nicola, Cornelius Fritz, Marius Mehrl +1
Networks are ubiquitous in economic research on organizations, trade, and many other areas. However, while economic theory extensively considers networks, no general framework for…
Exponential Random Graph Models for Dynamic Signed Networks: An Application to International Relations
Cornelius Fritz, Marius Mehrl, Paul W. Thurner +1
Substantive research in the Social Sciences regularly investigates signed networks, where edges between actors are either positive or negative. For instance, schoolchildren can be…
Statistical modelling of COVID-19 data: Putting Generalised Additive Models to work
Cornelius Fritz, Giacomo De Nicola, Martje Rave +5
Over the course of the COVID-19 pandemic, Generalised Additive Models (GAMs) have been successfully employed on numerous occasions to obtain vital data-driven insights. In this pap…
All that Glitters is not Gold: Relational Events Models with Spurious Events
Cornelius Fritz, Marius Mehrl, Paul W. Thurner +1
As relational event models are an increasingly popular model for studying relational structures, the reliability of large-scale event data collection becomes more and more importan…
Regional now- and forecasting for data reported with delay: Towards surveillance of COVID-19 infections
Giacomo De Nicola, Marc Schneble, Göran Kauermann +1
Governments around the world continue to act to contain and mitigate the spread of COVID-19. The rapidly evolving situation compels officials and executives to continuously adapt p…