TY - BOOK A1 - Laack, Walter van T1 - Greater Than the Entire Universe Y1 - 2022 SN - 978-3-936624-52-6 PB - van Laack GmbH CY - Aachen ER - TY - BOOK A1 - Laack, Walter van T1 - Aufruf zum Nachdenken: Corona und neue Kriege – Wie kann die Menschheit überleben? T1 - Call for Reflection: Corona and New Wars – How can Mankind survive? Y1 - 2022 SN - 978-3-936624-56-4 N1 - Dritter Band der Buchreihe “Vorträge & Einsichten – Lectures & Insights” und hier das zweite “Upside-Down-Buch”: Deutsche und englische Version in einem Buch. PB - van Laack GmbH CY - Aachen ER - TY - BOOK A1 - Laack, Walter van T1 - Schnittstelle Tod: Was lernen wir durch Corona über Leben und Tod? Y1 - 2022 SN - 978-3-936624-53-3 N1 - Siebter Tagungsband aus der Buchreihe “Schnittstelle Tod” PB - van Laack GmbH CY - Aachen ER - TY - CHAP A1 - Gömmel, Andreas A1 - Frauenrath, Tobias A1 - Otten, Mario A1 - Niendorf, Thoralf A1 - Butenweg, Christoph ED - Möser, Michael ED - Schulte-Fortkamp, Brgitte ED - Ochmann, Martin T1 - In-vivo measurements of vocal fold geometry using Magnetic Resonance Imaging T2 - Fortschritte der Akustik - DAGA 2010, 36. Jahrestagung für Akustik Y1 - 2010 SN - 978-3-9808659-8-2 PB - Deutsche Gesellschaft für Akustik CY - Berlin ER - TY - JOUR A1 - Schöning, Michael Josef A1 - Bronder, Thomas A1 - Wu, Chunsheng A1 - Scheja, Sabrina A1 - Jessing, Max A1 - Metzger-Boddien, Christoph A1 - Keusgen, Michael A1 - Poghossian, Arshak T1 - Label-Free DNA Detection with Capacitive Field-Effect Devices—Challenges and Opportunities JF - Proceedings N2 - Field-effect EIS (electrolyte-insulator-semiconductor) sensors modified with a positively charged weak polyelectrolyte layer have been applied for the electrical detection of DNA (deoxyribonucleic acid) immobilization and hybridization by the intrinsic molecular charge. The EIS sensors are able to detect the existence of target DNA amplicons in PCR (polymerase chain reaction) samples and thus, can be used as tool for a quick verification of DNA amplification and the successful PCR process. Due to their miniaturized setup, compatibility with advanced micro- and nanotechnologies, and ability to detect biomolecules by their intrinsic molecular charge, those sensors can serve as possible platform for the development of label-free DNA chips. Possible application fields as well as challenges and limitations will be discussed. Y1 - 2017 U6 - https://doi.org/10.3390/proceedings1080719 SN - 2504-3900 N1 - This article belongs to the Proceedings of "Proceedings of the 5th International Symposium on Sensor Science (I3S 2017)" VL - 1 IS - 8 SP - Artikel 719 PB - MDPI CY - Basel ER - TY - JOUR A1 - Gaigall, Daniel T1 - Testing marginal homogeneity of a continuous bivariate distribution with possibly incomplete paired data JF - Metrika N2 - 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. KW - Marginal homogeneity test KW - Crámer–von-Mises distance KW - Paired sample KW - Incomplete data KW - Resampling test Y1 - 2019 U6 - https://doi.org/10.1007/s00184-019-00742-5 SN - 1435-926X VL - 2020 IS - 83 SP - 437 EP - 465 PB - Springer ER - TY - JOUR A1 - Gaigall, Daniel T1 - Rothman–Woodroofe symmetry test statistic revisited JF - Computational Statistics & Data Analysis N2 - 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. Y1 - 2020 U6 - https://doi.org/10.1016/j.csda.2019.106837 SN - 0167-9473 VL - 2020 IS - 142 SP - Artikel 106837 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Baringhaus, Ludwig A1 - Gaigall, Daniel T1 - On an asymptotic relative efficiency concept based on expected volumes of confidence regions JF - Statistics - A Journal of Theoretical and Applied Statistic N2 - The paper deals with an asymptotic relative efficiency concept for confidence regions of multidimensional parameters that is based on the expected volumes of the confidence regions. Under standard conditions the asymptotic relative efficiencies of confidence regions are seen to be certain powers of the ratio of the limits of the expected volumes. These limits are explicitly derived for confidence regions associated with certain plugin estimators, likelihood ratio tests and Wald tests. Under regularity conditions, the asymptotic relative efficiency of each of these procedures with respect to each one of its competitors is equal to 1. The results are applied to multivariate normal distributions and multinomial distributions in a fairly general setting. KW - Volume of confidence regions KW - asymptotic relative efficiency KW - likelihood ratio test KW - multivariate normal distribution KW - multinomial distribution Y1 - 2019 U6 - https://doi.org/10.1080/02331888.2019.1683560 SN - 1029-4910 VL - 53 IS - 6 SP - 1396 EP - 1436 PB - Taylor & Francis CY - London ER - TY - JOUR A1 - Gaigall, Daniel T1 - On a new approach to the multi-sample goodness-of-fit problem JF - Communications in Statistics - Simulation and Computation N2 - Suppose we have k samples X₁,₁,…,X₁,ₙ₁,…,Xₖ,₁,…,Xₖ,ₙₖ with different sample sizes ₙ₁,…,ₙₖ and unknown underlying distribution functions F₁,…,Fₖ as observations plus k families of distribution functions {G₁(⋅,ϑ);ϑ∈Θ},…,{Gₖ(⋅,ϑ);ϑ∈Θ}, each indexed by elements ϑ from the same parameter set Θ, we consider the new goodness-of-fit problem whether or not (F₁,…,Fₖ) belongs to the parametric family {(G₁(⋅,ϑ),…,Gₖ(⋅,ϑ));ϑ∈Θ}. New test statistics are presented and a parametric bootstrap procedure for the approximation of the unknown null distributions is discussed. Under regularity assumptions, it is proved that the approximation works asymptotically, and the limiting distributions of the test statistics in the null hypothesis case are determined. Simulation studies investigate the quality of the new approach for small and moderate sample sizes. Applications to real-data sets illustrate how the idea can be used for verifying model assumptions. KW - Goodness-of-fit test KW - Multi-sample problem KW - Parametric bootstrap Y1 - 2019 U6 - https://doi.org/10.1080/03610918.2019.1618472 SN - 1532-4141 VL - 53 IS - 10 SP - 2971 EP - 2989 PB - Taylor & Francis CY - London ER - TY - JOUR A1 - Ditzhaus, Marc A1 - Gaigall, Daniel T1 - A consistent goodness-of-fit test for huge dimensional and functional data JF - Journal of Nonparametric Statistics N2 - A nonparametric goodness-of-fit test for random variables with values in a separable Hilbert space is investigated. To verify the null hypothesis that the data come from a specific distribution, an integral type test based on a Cramér-von-Mises statistic is suggested. The convergence in distribution of the test statistic under the null hypothesis is proved and the test's consistency is concluded. Moreover, properties under local alternatives are discussed. Applications are given for data of huge but finite dimension and for functional data in infinite dimensional spaces. A general approach enables the treatment of incomplete data. In simulation studies the test competes with alternative proposals. KW - Cramér-von-Mises statistic KW - separable Hilbert space KW - huge dimensional data KW - functional data Y1 - 2018 U6 - https://doi.org/10.1080/10485252.2018.1486402 SN - 1029-0311 VL - 30 IS - 4 SP - 834 EP - 859 PB - Taylor & Francis CY - Abingdon ER -