Refine
Year of publication
- 2020 (59) (remove)
Institute
- Fachbereich Medizintechnik und Technomathematik (59) (remove)
Has Fulltext
- no (59) (remove)
Document Type
- Article (44)
- Part of a Book (7)
- Conference Proceeding (4)
- Doctoral Thesis (2)
- Book (1)
- Other (1)
Keywords
- Adaptive control (1)
- Brownian Pillow (1)
- Choleratoxin B (1)
- Conservation laws (1)
- Crámer–von-Mises distance (1)
- Dimensional splitting (1)
- Entropy solution (1)
- Exponential time differencing (1)
- Finite difference methods (1)
- Higher-order codes (1)
- Hoeffding-Blum-Kiefer-Rosenblatt independence test (1)
- Implicit methods (1)
- Incomplete data (1)
- Interior transmission eigenvalues (1)
- Iterative learning control (1)
- Marginal homogeneity test (1)
- Matrix exponential (1)
- Monotone methods (1)
- Multi-dimensional partial differential equations (1)
- Nonlinear PDEs (1)
- Paired sample (1)
- Reaction-diffusion systems (1)
- Real distinct pole (1)
- Resampling test (1)
- Robotic rehabilitation (1)
- Source term (1)
- Trinkwassersicherheit (1)
- agility (1)
- cholera toxin B (1)
- community dwelling (1)
- drinking water safety (1)
- elastic scattering (1)
- healthy aging (1)
- magnetic frequency mixing technique (1)
- method of fundamental solutions (1)
- not identically distributed (1)
- prevention (1)
- psychosocial (1)
- random effects meta-regression model (1)
Is part of the Bibliography
- no (59)
The Rothman–Woodroofe symmetry test statistic is revisited on the basis of independent but not necessarily identically distributed random variables. The distribution-freeness if the underlying distributions are all symmetric and continuous is obtained. The results are applied for testing symmetry in a meta-analysis random effects model. The consistency of the procedure is discussed in this situation as well. A comparison with an alternative proposal from the literature is conducted via simulations. Real data are analyzed to demonstrate how the new approach works in practice.
We discuss the testing problem of homogeneity of the marginal distributions of a continuous bivariate distribution based on a paired sample with possibly missing components (missing completely at random). Applying the well-known two-sample Crámer–von-Mises distance to the remaining data, we determine the limiting null distribution of our test statistic in this situation. It is seen that a new resampling approach is appropriate for the approximation of the unknown null distribution. We prove that the resulting test asymptotically reaches the significance level and is consistent. Properties of the test under local alternatives are pointed out as well. Simulations investigate the quality of the approximation and the power of the new approach in the finite sample case. As an illustration we apply the test to real data sets.
Twee Kanten van één Medaille
(2020)
Elastic transmission eigenvalues and their computation via the method of fundamental solutions
(2020)
A stabilized version of the fundamental solution method to catch ill-conditioning effects is investigated with focus on the computation of complex-valued elastic interior transmission eigenvalues in two dimensions for homogeneous and isotropic media. Its algorithm can be implemented very shortly and adopts to many similar partial differential equation-based eigenproblems as long as the underlying fundamental solution function can be easily generated. We develop a corroborative approximation analysis which also implicates new basic results for transmission eigenfunctions and present some numerical examples which together prove successful feasibility of our eigenvalue recovery approach.
In this article, a concept of implicit methods for scalar conservation laws in one or more spatial dimensions allowing also for source terms of various types is presented. This material is a significant extension of previous work of the first author (Breuß SIAM J. Numer. Anal. 43(3), 970–986 2005). Implicit notions are developed that are centered around a monotonicity criterion. We demonstrate a connection between a numerical scheme and a discrete entropy inequality, which is based on a classical approach by Crandall and Majda. Additionally, three implicit methods are investigated using the developed notions. Next, we conduct a convergence proof which is not based on a classical compactness argument. Finally, the theoretical results are confirmed by various numerical tests.
The established Hoeffding-Blum-Kiefer-Rosenblatt independence test statistic is investigated for partly not identically distributed data. Surprisingly, it turns out that the statistic has the well-known distribution-free limiting null distribution of the classical criterion under standard regularity conditions. An application is testing goodness-of-fit for the regression function in a non parametric random effects meta-regression model, where the consistency is obtained as well. Simulations investigate size and power of the approach for small and moderate sample sizes. A real data example based on clinical trials illustrates how the test can be used in applications.
Interior transmission eigenvalue problems for the Helmholtz equation play an important role in inverse wave scattering. Some distribution properties of those eigenvalues in the complex plane are reviewed. Further, a new scattering model for the interior transmission eigenvalue problem with mixed boundary conditions is described and an efficient algorithm for computing the interior transmission eigenvalues is proposed. Finally, extensive numerical results for a variety of two-dimensional scatterers are presented to show the validity of the proposed scheme.
We present new numerical results for shape optimization problems of interior Neumann eigenvalues. This field is not well understood from a theoretical standpoint. The existence of shape maximizers is not proven beyond the first two eigenvalues, so we study the problem numerically. We describe a method to compute the eigenvalues for a given shape that combines the boundary element method with an algorithm for nonlinear eigenvalues. As numerical optimization requires many such evaluations, we put a focus on the efficiency of the method and the implemented routine. The method is well suited for parallelization. Using the resulting fast routines and a specialized parametrization of the shapes, we found improved maxima for several eigenvalues.