Projects
An adjoint method for combined robust optimization, error estimation and uncertainty quantification CFD. Vrije Universiteit Brussel
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Robust inference techniques based on resampling KU Leuven
Linear regression is the most famous type of regression analysis in statistics. A statistical analysis of a linear regression model usually begins with estimation of the regression coefficients and continues with measuring the accuracy of the estimators. Unfortunately, it is well known that a traditional statistical analysis based on the least squares principle is very sensitive to outliers in the data. Although many robust estimators have ...
Robust and sparse statistical methods for actuarial sciences KU Leuven
This PhD thesis consists of two parts and in the first part, we focus on robust statistics. More specifically, we consider robust regression when the response variable follows a distribution in the double exponential family. Hence, by means of a generalized linear model (GLM) based on covariates, we will robustly estimate the expected value as well as the dispersion. The latter itself can be of interest, but taking the dispersion into account ...
Robust nonparametric methods for functional data KU Leuven
This thesis presents three novel statistical methods for the robust analysis of functional data and theoretical insights into two pre-existing nonparametric
regression methods, namely regression with penalized and smoothing splines. Beginning from Chapter 2, we review the functional linear regression paradigm
and propose a two step-estimation procedure that combines robust functional principal components and robust linear ...
Development and implementation of real-time, robust statistical methods with novel applications in food sorting KU Leuven
In industrial food sorting, fast sensor based technologies are used for automated food inspection. These sensors typically produce multivariate data that are used as input for classification algorithms, which are responsible for the detection of commonly found defects among the regular material. Typically, huge amounts of product are scanned in an automated fashion. Food inspection machines therefore generate gigabytes of multivariate data in ...
Robust techniques for functional data and generalized linear models KU Leuven
Robust estimators are indispensable tools in statistics. Frequently, a (small) part of the data sample follows a different pattern as the majority of the data or even no pattern at all. Such atypical observations are called outliers. They may be simple gross errors such as measurement errors or copying mistakes. However, they may also be observations governed by different laws or indicate subgroups or structures in the data sample.
Two ...
Passenger Robust Timetables for Dense Railway Networks KU Leuven
Delays and unreliable travel times are daily practice and unavoidable in public transport. Furthermore, manual decisions are still omnipresent in planning processes and real time dispatching. Nevertheless, the planning of public transport affects the performance and the popularity of these transport modes and the sustainability of the transport system as a whole. Therefore, investigating how public transport can benefit from decision support ...
Analysis of discretely sampled functional data based on robust estimation of dispersion. KU Leuven
Estimating dispersion is a central problem in functional/longitudinal data analysis, yet most current estimation procedures either unrealistically assume completely observed trajectories or lack robustness with respect to the many kinds of anomalies one can encounter in the functional setting. To remedy these deficiencies we introduce a family of resistant dispersion estimators from discretely sampled functional data. The proposed method ...
Robust vibration serviceability design of structures subjected to human-induced loading. KU Leuven
The use of high strength materials and advanced calculation methods facilitates the design of slender footbridges, often resulting in low natural frequencies of the structure in the range of the loading frequencies of human-induced excitation. In combination with a low modal damping, these structures are sensitive to human-induced loading. Therefore, a vibration serviceability assessment of structures subjected to human-induced loading has ...