Publications
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Correcting the bias of the net benefit estimator due to right-censored observations Hasselt University
Generalized pairwise comparisons (GPCs) are a statistical method used in randomized clinical trials to simultaneously analyze several prioritized outcomes. This procedure estimates the net benefit (Delta). Delta may be interpreted as the probability for a random patient in the treatment group to have a better overall outcome than a random patient in the control group, minus the probability of the opposite situation. However, the presence of ...
Improved dynamic behaviour of a sensorless stepping motor load angle estimator based on Transfer Function Analyzer technique University of Antwerp Ghent University
The performance and robustness of a sensorless controller strongly depends on how quickly and accurately the feedback is obtained. For this reason, the purpose of this paper is to introduce an improved load angle estimator that provides feedback on the ability of the stepping motor to follow the imposed position/speed setpoint. The novel estimation dynamics is compared theoretically and experimentally with dynamics of similar estimators.
The capitalization of CAP payments into land rental prices: a grouped fixed-effects estimator KU Leuven
Background: The current study examined whether test-related reassurance seeking is associated with lower scores on a high stakes, standardized test (i.e., the ACT) after controlling for academic performance in high school, and with spoiled answers (i.e., changing correct answers to incorrect) on a subsequent academic exam. Method: Students (N = 59) completed measures of test-related reassurance seeking behavior, other test anxiety-related ...
The minimum regularized covariance determinant estimator Vrije Universiteit Brussel University of Antwerp KU Leuven Ghent University
The minimum covariance determinant (MCD) approach estimates the location and scatter matrix using the subset of given size with lowest sample covariance determinant. Its main drawback is that it cannot be applied when the dimension exceeds the subset size. We propose the minimum regularized covariance determinant (MRCD) approach, which differs from the MCD in that the scatter matrix is a convex combination of a target matrix and the sample ...
Image denoising based on nonlocal Bayesian singular value thresholding and Stein's unbiased risk estimator KU Leuven
Singular value thresholding (SVT)- or nuclear norm minimization (NNM)-based nonlocal image denoising methods often rely on the precise estimation of the noise variance. However, most existing methods either assume that the noise variance is known or require an extra step to estimate it. Under the iterative regularization framework, the error in the noise variance estimate propagates and accumulates with each iteration, ultimately degrading the ...
An imprecise probabilistic estimator for the transition rate matrix of a continuous-time Markov Chain Ghent University
We consider the problem of estimating the transition rate matrix of a continuous-time Markov chain from a finite-duration realisation of this process. We approach this problem in an imprecise probabilistic framework, using a set of prior distributions on the unknown transition rate matrix. The resulting estimator is a set of transition rate matrices that, for reasons of conjugacy, is easy to find. To determine the hyperparameters for our set of ...