activity
20162022
most citedMixture Models and Networks -- Overview of Stochastic Blockmodelling

1 citations · 2 across the 6 of their papers we have counts for

collaborators

14 papers

physics.soc-ph2022

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…

stat.AP2021

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…

stat.AP2021

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…

stat.ME20211 cited

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…

stat.ME20201 cited

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…

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…