< Back to previous page

Project

Asymptotic theory for multidimensional statistics.

Mathematical statistics provides support for data-based decisions in a variety of fields such as (bio)medical sciences, actuarial sciences, financial mathematics, biology, bioinformatics, engineering, etc. The current research questions in statistics require highly advanced techniques, they are needed to understand and to deal with the contemporary issues such as high or ultra-high dimensional data, functional or spatial data, and many sorts of 'nonperfect' data (data measured with error, incomplete data, censored or truncated data). Important research topics are: the development of estimators and tests in high-dimensional settings; dimension reduction; clustering and classification methods; the study of flexible non- and semiparametric models; goodness-of-fit tests and diagnostics for complex models; a study of dependence structures. Specific emphasis will be put on measurement error and inverse problems and on survival data. Moving beyond the current stage of knowledge requires a combination of theoretical skills. Therefore a group of national international researchers will join forces in this scientific network.
Date:1 Jan 2012 →  31 Dec 2018
Keywords:High-dimensional data, Asymptotic theory, Statistics, Nonparametric methods, Dependence, Survival data
Disciplines:Applied economics, Economic history, Macroeconomics and monetary economics, Microeconomics, Tourism