PhD in Business Engineering

The PhD researcher will be part of a very active research group in mathematical statistics, consisting of members of the research group ORSTAT at the Faculty of Economics and Business, and members of the section Statistics and Risk, Department of Mathematics, Faculty of Science at KU Leuven in Leuven, Belgium./nThe project contributes in developing new statistical methodologies for data belonging to non-Euclidean spaces. It in particular deals with data on a circle, a hypersphere, a torus. Such data are omnipresent in applications (e.g. wind directions or orientations, escape directions of animals, ...). Most applications often even involve a mix of Euclidean data (real-valued data) and non-Euclidean data, and hence developed methods should preferably be able to deal with a diversity of data (possibly in high-dimensional settings)./nFurthermore, when developing appropriate statistical methods, one should avoid making unrealistic (too restrictive) assumptions. This calls for flexible modelling and inference, i.e. semiparametric or nonparametric methods, for directional data./nPractical implementation of the developed methods (via codes written in open source software, such as R, Python, ...) is part of the project.