@article{MolkenthinDonnerReichetal.2022,
  author    = {Molkenthin, Christian and Donner, Christian and Reich, Sebastian and Z{\"o}ller, Gert and Hainzl, Sebastian and Holschneider, Matthias and Opper, Manfred},
  title     = {GP-ETAS: semiparametric Bayesian inference for the spatio-temporal epidemic type aftershock sequence model},
  series = {Statistics and Computing},
  volume    = {32},
  journal   = {Statistics and Computing},
  number    = {2},
  publisher = {Springer},
  address   = {Dordrecht},
  issn      = {0960-3174},
  doi       = {10.1007/s11222-022-10085-3},
  pages     = {25},
  year      = {2022},
  abstract  = {The spatio-temporal epidemic type aftershock sequence (ETAS) model is widely used to describe the self-exciting nature of earthquake occurrences. While traditional inference methods provide only point estimates of the model parameters, we aim at a fully Bayesian treatment of model inference, allowing naturally to incorporate prior knowledge and uncertainty quantification of the resulting estimates. Therefore, we introduce a highly flexible, non-parametric representation for the spatially varying ETAS background intensity through a Gaussian process (GP) prior. Combined with classical triggering functions this results in a new model formulation, namely the GP-ETAS model. We enable tractable and efficient Gibbs sampling by deriving an augmented form of the GP-ETAS inference problem. This novel sampling approach allows us to assess the posterior model variables conditioned on observed earthquake catalogues, i.e., the spatial background intensity and the parameters of the triggering function. Empirical results on two synthetic data sets indicate that GP-ETAS outperforms standard models and thus demonstrate the predictive power for observed earthquake catalogues including uncertainty quantification for the estimated parameters. Finally, a case study for the l'Aquila region, Italy, with the devastating event on 6 April 2009, is presented.},
  language  = {en}
}
@phdthesis{Schmider2021,
  author    = {Schmider, Stephan},
  title     = {Was ist HipHop?},
  doi       = {10.25932/publishup-52375},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-523759},
  school      = {Universit{\"a}t Potsdam},
  pages     = {225},
  year      = {2021},
  abstract  = {Es handelt sich bei der vorliegenden Dissertation um eine investigative Forschungsarbeit, die sich mit dem dynamisch wandelnden HipHop-Ph{\"a}nomen befasst. Der Autor erl{\"a}utert hierbei die anhaltende Attraktivit{\"a}t des kulturellen Ph{\"a}nomens HipHop und versucht die Tatsache der stetigen Reproduzierbarkeit des HipHops genauer zu erkl{\"a}ren. Daher beginnt er mit einer historischen Diskursanalyse der HipHop-Kultur. Er analysiert hierf{\"u}r die Formen, die Protagonisten und die Diskurse des HipHops, um diesen besser verstehen zu k{\"o}nnen. Durch die Herausarbeitung der genuinen Eigenschaft der Mehrfachkodierbarkeit des HipHops werden g{\"a}ngige Erkl{\"a}rungsmuster aus Wissenschaft und Medien relativiert und kritisiert. Der Autor kombiniert in seiner Studie kultur- und erziehungswissenschaftliche Literatur mit diversen aktuellen und historischen Darstellungen und Bildern. Es werden vor allem bildbasierte Selbstinszenierungen von HipHoppern und Selbstzeugnisse aus narrativen Interviews, die er selbst mit verschiedenen HipHoppern in Deutschland gef{\"u}hrt hat, ausgewertet. Neben den narrativen Interviews dient vor allem die Bildinterpretation nach Bohnsack als Quelle zur Bildung der These der Mehrfachkodierbarkeit. Hierbei werden zwei Bilder der HipHopper Lady Bitch Ray und Kollegah nach Bohnsack (2014) interpretiert und gezeigt wie HipHop neben der lyrischen und der klanglichen Komponente auch visuell inszeniert und produziert wird. Hieraus wird geschlussfolgert, dass es im HipHop m{\"o}glich ist kontr{\"a}re Sichtweisen bei gleichzeitiger Anwendung von typischen Kulturpraktiken wie zum Beispiel dem Boasting darzustellen und zu vermitteln. Die stetige Offenheit des HipHops wird durch Praktiken wie dem Sampling oder dem Battle deutlich und der Autor erkl{\"a}rt, dass durch diese Techniken die generative Eigenschaft der Mehrfachkodierbarkeit hergestellt wird. Damit vertritt er eine Art Baukasten-Theorie, die besagt, dass sich prinzipiell jeder aus dem Baukasten HipHop, je nach Vorliebe, Interesse und Affinit{\"a}t, bedienen kann. Durch die Vielfalt an Meinungen zu HipHop, die der Autor durch die Kodierung der gef{\"u}hrten narrativen Interviews erh{\"a}lt, wird diese These verdeutlicht und es wird klar, dass es sich bei HipHop um mehr als nur eine Mode handelt. HipHop besitzt die prinzipielle M{\"o}glichkeit durch die Offenheit, die er in sich tr{\"a}gt, sich stetig neu zu wandeln und damit an Beliebtheit und Popularit{\"a}t zuzunehmen. Die vorliegende Arbeit erweitert damit die immer gr{\"o}ßer werdende Forschung in den HipHop-Studies und setzt wichtige Akzente um weiter zu forschen und HipHop besser verst{\"a}ndlich zu machen.},
  language  = {de}
}
@article{VossZimmermannZimmermann2016,
  author    = {Voss, Sebastian and Zimmermann, Beate and Zimmermann, Alexander},
  title     = {Detecting spatial structures in throughfall data: The effect of extent, sample size, sampling design, and variogram estimation method},
  series = {Journal of hydrology},
  volume    = {540},
  journal   = {Journal of hydrology},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0022-1694},
  doi       = {10.1016/j.jhydrol.2016.06.042},
  pages     = {527 -- 537},
  year      = {2016},
  abstract  = {In the last decades, an increasing number of studies analyzed spatial patterns in throughfall by means of variograms. The estimation of the variogram from sample data requires an appropriate sampling scheme: most importantly, a large sample and a layout of sampling locations that often has to serve both variogram estimation and geostatistical prediction. While some recommendations on these aspects exist, they focus on Gaussian data and high ratios of the variogram range to the extent of the study area. However, many hydrological data, and throughfall data in particular, do not follow a Gaussian distribution. In this study, we examined the effect of extent, sample size, sampling design, and calculation method on variogram estimation of throughfall data. For our investigation, we first generated non Gaussian random fields based on throughfall data with large outliers. Subsequently, we sampled the fields with three extents (plots with edge lengths of 25 m, 50 m, and 100 m), four common sampling designs (two grid-based layouts, transect and random sampling) and five sample sizes (50, 100, 150, 200, 400). We then estimated the variogram parameters by method-of-moments (non-robust and robust estimators) and residual maximum likelihood. Our key findings are threefold. First, the choice of the extent has a substantial influence on the estimation of the variogram. A comparatively small ratio of the extent to the correlation length is beneficial for variogram estimation. Second, a combination of a minimum sample size of 150, a design that ensures the sampling of small distances and variogram estimation by residual maximum likelihood offers a good compromise between accuracy and efficiency. Third, studies relying on method-of-moments based variogram estimation may have to employ at least 200 sampling points for reliable variogram estimates. These suggested sample sizes exceed the number recommended by studies dealing with Gaussian data by up to 100 \%. Given that most previous through fall studies relied on method-of-moments variogram estimation and sample sizes <<200, currently available data are prone to large uncertainties. (C) 2016 Elsevier B.V. All rights reserved.},
  language  = {en}
}
@article{ZimmermannVossMetzgeretal.2016,
  author    = {Zimmermann, Alexander and Voss, Sebastian and Metzger, Johanna Clara and Hildebrandt, Anke and Zimmermann, Beate},
  title     = {estimating mean throughfall},
  series = {Journal of hydrology},
  volume    = {542},
  journal   = {Journal of hydrology},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0022-1694},
  doi       = {10.1016/j.jhydrol.2016.09.047},
  pages     = {781 -- 789},
  year      = {2016},
  abstract  = {The selection of an appropriate spatial extent of a sampling plot is one among several important decisions involved in planning a throughfall sampling scheme. In fact, the choice of the extent may determine whether or not a study can adequately characterize the hydrological fluxes of the studied ecosystem. Previous attempts to optimize throughfall sampling schemes focused on the selection of an appropriate sample size, support, and sampling design, while comparatively little attention has been given to the role of the extent. In this contribution, we investigated the influence of the extent on the representativeness of mean throughfall estimates for three forest ecosystems of varying stand structure. Our study is based on virtual sampling of simulated throughfall fields. We derived these fields from throughfall data sampled in a simply structured forest (young tropical forest) and two heterogeneous forests (old tropical forest, unmanaged mixed European beech forest). We then sampled the simulated throughfall fields with three common extents and various sample sizes for a range of events and for accumulated data. Our findings suggest that the size of the study area should be carefully adapted to the complexity of the system under study and to the required temporal resolution of the throughfall data (i.e. event-based versus accumulated). Generally, event-based sampling in complex structured forests (conditions that favor comparatively long autocorrelations in throughfall) requires the largest extents. For event-based sampling, the choice of an appropriate extent can be as important as using an adequate sample size. (C) 2016 Elsevier B.V. All rights reserved.},
  language  = {en}
}