GRK 1953: Statistical Modelling of Complex Systems and Processes - Advanced Nonparametric Approaches

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The field of statistics is currently undergoing drastic change. Driven by the development in applications, more and more massive and very complex data sets have become available ("big data"). Examples are the fast-growing data sets in meteorology, the data sets from high-frequency finance where data are recorded and analyzed at the frequency of a millisecond, and of course new technologies in autonomous driving and social networks. These huge data sets require a change in statistical methods for analyzing such data – for example new methods for data whose dimension is extremely large, or new methods for financial data which can be performed online in milliseconds. The new statistical methodology includes techniques for high-dimensional models and dimension reduction, inference on the structure of underlying models and structural nonparametric modeling, and flexible modeling of dependencies for spatio-temporal data, stochastic networks and financial data. This research training group (RTG) will be devoted to fundamental research in the area of advanced nonparametric statistical modeling of complex stochastic systems and processes. Here, fundamental research means both the development and the mathematical investigation of new methodologies, which is essential for a thorough understanding of complex situations. Current work in this area makes use of deep theoretical developments in probability theory and mathematical statistics. Therefore, a broad knowledge of modern strands of probability and mathematical statistics is necessary. The main intention of the RTG is to offer young doctoral researchers an advanced mathematical basis and international contacts for their research at the frontier of modern theoretical statistics.