Research

The research areas in which the members of the Institute of statistics are working are very diverse.  The main areas of expertise are non-and semiparametric regression techniques, time series analysis, survival analysis, industrial statistics, extreme value analysis and statistics for the actuarial sciences.

In the context of non- and semiparametric regression, the Institute is a leading expert in the area of frontier estimation, and in particular in the application of non- and semiparametric approaches for this problem in the context of efficiency analysis. A lot of research is also carried out in the context of inverse problems in econometrics, and its applications in instrumental regression and deconvolution problems. The study of semiparametric regression models (e.g.\ single index models, partial linear models) and of nonparametric location-scale models, is another area in which the Institute is taking a leading role.  Denoising and functional image clustering by means of wavelets are also investigated.

The analysis of time series is a second cornerstone of the research activities at the Institute.  The focus lies on the modelling and analysis of non-stationary time series,  multivariate (high-dimensional) time series, factor models, volatility models, spectral density estimation and goodness-of-fit methods.  Also, applications in statistical signal processing, and biomedical, economical and financial time series are studied.

The analysis of data coming from medical or industrial studies is also a research topic to which much attention is paid at the Institute.  Medical data are often subject to censoring (survival analysis).  The non- and semiparametric modelling of this type of data is studied in detail, both the asymptotics for these models, as the application to medical data.  In the context of industrial statistics, the focus lies on experimental design and multicriteria optimisation with applications in drug discovery, and on the analysis and modelling of time intensity curves in sensometrics.

The development of methods for extreme value analysis is also of interest at the Institute : modelling of extremes in univariate and multivariate time series, and in particular in Markov chains. The modelling of dependence by means of copulas, the development of stochastic inequalities (stochastic orders, stochastic extrema), and the application of statistical concepts to the research area of insurance are also investigated.