@article{Gaigall2021, author = {Gaigall, Daniel}, title = {Test for Changes in the Modeled Solvency Capital Requirement of an Internal Risk Model}, series = {ASTIN Bulletin}, volume = {51}, journal = {ASTIN Bulletin}, number = {3}, publisher = {Cambridge Univ. Press}, address = {Cambridge}, issn = {1783-1350}, doi = {10.1017/asb.2021.20}, pages = {813 -- 837}, year = {2021}, abstract = {In the context of the Solvency II directive, the operation of an internal risk model is a possible way for risk assessment and for the determination of the solvency capital requirement of an insurance company in the European Union. A Monte Carlo procedure is customary to generate a model output. To be compliant with the directive, validation of the internal risk model is conducted on the basis of the model output. For this purpose, we suggest a new test for checking whether there is a significant change in the modeled solvency capital requirement. Asymptotic properties of the test statistic are investigated and a bootstrap approximation is justified. A simulation study investigates the performance of the test in the finite sample case and confirms the theoretical results. The internal risk model and the application of the test is illustrated in a simplified example. The method has more general usage for inference of a broad class of law-invariant and coherent risk measures on the basis of a paired sample.}, language = {en} } @article{Gaigall2020, author = {Gaigall, Daniel}, title = {Testing marginal homogeneity of a continuous bivariate distribution with possibly incomplete paired data}, series = {Metrika}, volume = {2020}, journal = {Metrika}, number = {83}, publisher = {Springer}, issn = {1435-926X}, doi = {10.1007/s00184-019-00742-5}, pages = {437 -- 465}, year = {2020}, abstract = {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 Cr{\´a}mer-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.}, language = {en} } @article{Gaigall2020, author = {Gaigall, Daniel}, title = {Hoeffding-Blum-Kiefer-Rosenblatt independence test statistic on partly not identically distributed data}, series = {Communications in Statistics - Theory and Methods}, volume = {51}, journal = {Communications in Statistics - Theory and Methods}, number = {12}, publisher = {Taylor \& Francis}, address = {London}, issn = {1532-415X}, doi = {10.1080/03610926.2020.1805767}, pages = {4006 -- 4028}, year = {2020}, abstract = {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.}, language = {en} } @article{GaigallGerstenbergTrinh2022, author = {Gaigall, Daniel and Gerstenberg, Julian and Trinh, Thi Thu Ha}, title = {Empirical process of concomitants for partly categorial data and applications in statistics}, series = {Bernoulli}, volume = {28}, journal = {Bernoulli}, number = {2}, publisher = {International Statistical Institute}, address = {Den Haag, NL}, issn = {1573-9759}, doi = {10.3150/21-BEJ1367}, pages = {803 -- 829}, year = {2022}, abstract = {On the basis of independent and identically distributed bivariate random vectors, where the components are categorial and continuous variables, respectively, the related concomitants, also called induced order statistic, are considered. The main theoretical result is a functional central limit theorem for the empirical process of the concomitants in a triangular array setting. A natural application is hypothesis testing. An independence test and a two-sample test are investigated in detail. The fairly general setting enables limit results under local alternatives and bootstrap samples. For the comparison with existing tests from the literature simulation studies are conducted. The empirical results obtained confirm the theoretical findings.}, language = {en} } @article{DitzhausGaigall2022, author = {Ditzhaus, Marc and Gaigall, Daniel}, title = {Testing marginal homogeneity in Hilbert spaces with applications to stock market returns}, series = {Test}, volume = {2022}, journal = {Test}, number = {31}, publisher = {Springer}, issn = {1863-8260}, doi = {10.1007/s11749-022-00802-5}, pages = {749 -- 770}, year = {2022}, abstract = {This paper considers a paired data framework and discusses the question of marginal homogeneity of bivariate high-dimensional or functional data. The related testing problem can be endowed into a more general setting for paired random variables taking values in a general Hilbert space. To address this problem, a Cram{\´e}r-von-Mises type test statistic is applied and a bootstrap procedure is suggested to obtain critical values and finally a consistent test. The desired properties of a bootstrap test can be derived that are asymptotic exactness under the null hypothesis and consistency under alternatives. Simulations show the quality of the test in the finite sample case. A possible application is the comparison of two possibly dependent stock market returns based on functional data. The approach is demonstrated based on historical data for different stock market indices.}, language = {en} } @inproceedings{Gaigall2022, author = {Gaigall, Daniel}, title = {On Consistent Hypothesis Testing In General Hilbert Spaces}, series = {Proceedings of the 4th International Conference on Statistics: Theory and Applications (ICSTA'22)}, booktitle = {Proceedings of the 4th International Conference on Statistics: Theory and Applications (ICSTA'22)}, publisher = {Avestia Publishing}, address = {Orl{\´e}ans, Kanada}, doi = {10.11159/icsta22.157}, pages = {Paper No. 157}, year = {2022}, abstract = {Inference on the basis of high-dimensional and functional data are two topics which are discussed frequently in the current statistical literature. A possibility to include both topics in a single approach is working on a very general space for the underlying observations, such as a separable Hilbert space. We propose a general method for consistently hypothesis testing on the basis of random variables with values in separable Hilbert spaces. We avoid concerns with the curse of dimensionality due to a projection idea. We apply well-known test statistics from nonparametric inference to the projected data and integrate over all projections from a specific set and with respect to suitable probability measures. In contrast to classical methods, which are applicable for real-valued random variables or random vectors of dimensions lower than the sample size, the tests can be applied to random vectors of dimensions larger than the sample size or even to functional and high-dimensional data. In general, resampling procedures such as bootstrap or permutation are suitable to determine critical values. The idea can be extended to the case of incomplete observations. Moreover, we develop an efficient algorithm for implementing the method. Examples are given for testing goodness-of-fit in a one-sample situation in [1] or for testing marginal homogeneity on the basis of a paired sample in [2]. Here, the test statistics in use can be seen as generalizations of the well-known Cram{\´e}rvon-Mises test statistics in the one-sample and two-samples case. The treatment of other testing problems is possible as well. By using the theory of U-statistics, for instance, asymptotic null distributions of the test statistics are obtained as the sample size tends to infinity. Standard continuity assumptions ensure the asymptotic exactness of the tests under the null hypothesis and that the tests detect any alternative in the limit. Simulation studies demonstrate size and power of the tests in the finite sample case, confirm the theoretical findings, and are used for the comparison with concurring procedures. A possible application of the general approach is inference for stock market returns, also in high data frequencies. In the field of empirical finance, statistical inference of stock market prices usually takes place on the basis of related log-returns as data. In the classical models for stock prices, i.e., the exponential L{\´e}vy model, Black-Scholes model, and Merton model, properties such as independence and stationarity of the increments ensure an independent and identically structure of the data. Specific trends during certain periods of the stock price processes can cause complications in this regard. In fact, our approach can compensate those effects by the treatment of the log-returns as random vectors or even as functional data.}, language = {en} } @inproceedings{StaatTran2022, author = {Staat, Manfred and Tran, Ngoc Trinh}, title = {Strain based brittle failure criteria for rocks}, series = {Proceedings of (NACOME2022) The 11th National Conference on Mechanics, Vol. 1. Solid Mechanics, Rock Mechanics, Artificial Intelligence, Teaching and Training}, booktitle = {Proceedings of (NACOME2022) The 11th National Conference on Mechanics, Vol. 1. Solid Mechanics, Rock Mechanics, Artificial Intelligence, Teaching and Training}, publisher = {Nha xuat ban Khoa hoc tu nhien va Cong nghe (Verlag Naturwissenschaft und Technik)}, address = {Hanoi}, isbn = {978-604-357-084-7}, pages = {500 -- 509}, year = {2022}, abstract = {When confining pressure is low or absent, extensional fractures are typical, with fractures occurring on unloaded planes in rock. These "paradox" fractures can be explained by a phenomenological extension strain failure criterion. In the past, a simple empirical criterion for fracture initiation in brittle rock has been developed. But this criterion makes unrealistic strength predictions in biaxial compression and tension. A new extension strain criterion overcomes this limitation by adding a weighted principal shear component. The weight is chosen, such that the enriched extension strain criterion represents the same failure surface as the Mohr-Coulomb (MC) criterion. Thus, the MC criterion has been derived as an extension strain criterion predicting failure modes, which are unexpected in the understanding of the failure of cohesive-frictional materials. In progressive damage of rock, the most likely fracture direction is orthogonal to the maximum extension strain. The enriched extension strain criterion is proposed as a threshold surface for crack initiation CI and crack damage CD and as a failure surface at peak P. Examples show that the enriched extension strain criterion predicts much lower volumes of damaged rock mass compared to the simple extension strain criterion.}, language = {en} } @article{BaringhausGaigall2022, author = {Baringhaus, Ludwig and Gaigall, Daniel}, title = {A goodness-of-fit test for the compound Poisson exponential model}, series = {Journal of Multivariate Analysis}, volume = {195}, journal = {Journal of Multivariate Analysis}, number = {Article 105154}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0047-259X}, doi = {10.1016/j.jmva.2022.105154}, year = {2022}, abstract = {On the basis of bivariate data, assumed to be observations of independent copies of a random vector (S,N), we consider testing the hypothesis that the distribution of (S,N) belongs to the parametric class of distributions that arise with the compound Poisson exponential model. Typically, this model is used in stochastic hydrology, with N as the number of raindays, and S as total rainfall amount during a certain time period, or in actuarial science, with N as the number of losses, and S as total loss expenditure during a certain time period. The compound Poisson exponential model is characterized in the way that a specific transform associated with the distribution of (S,N) satisfies a certain differential equation. Mimicking the function part of this equation by substituting the empirical counterparts of the transform we obtain an expression the weighted integral of the square of which is used as test statistic. We deal with two variants of the latter, one of which being invariant under scale transformations of the S-part by fixed positive constants. Critical values are obtained by using a parametric bootstrap procedure. The asymptotic behavior of the tests is discussed. A simulation study demonstrates the performance of the tests in the finite sample case. The procedure is applied to rainfall data and to an actuarial dataset. A multivariate extension is also discussed.}, language = {en} } @article{TranTrinhDaoetal.2022, author = {Tran, Ngoc Trinh and Trinh, Tu Luc and Dao, Ngoc Tien and Giap, Van Tan and Truong, Manh Khuyen and Dinh, Thuy Ha and Staat, Manfred}, title = {FEM shakedown analysis of structures under random strength with chance constrained programming}, series = {Vietnam Journal of Mechanics}, volume = {44}, journal = {Vietnam Journal of Mechanics}, number = {4}, publisher = {Vietnam Academy of Science and Technology (VAST)}, issn = {0866-7136}, doi = {10.15625/0866-7136/17943}, pages = {459 -- 473}, year = {2022}, abstract = {Direct methods, comprising limit and shakedown analysis, are a branch of computational mechanics. They play a significant role in mechanical and civil engineering design. The concept of direct methods aims to determine the ultimate load carrying capacity of structures beyond the elastic range. In practical problems, the direct methods lead to nonlinear convex optimization problems with a large number of variables and constraints. If strength and loading are random quantities, the shakedown analysis can be formulated as stochastic programming problem. In this paper, a method called chance constrained programming is presented, which is an effective method of stochastic programming to solve shakedown analysis problems under random conditions of strength. In this study, the loading is deterministic, and the strength is a normally or lognormally distributed variable.}, language = {en} } @article{RuebbelkeVoegeleGrajewskietal.2022, author = {R{\"u}bbelke, Dirk and V{\"o}gele, Stefan and Grajewski, Matthias and Zobel, Luzy}, title = {Hydrogen-based steel production and global climate protection: An empirical analysis of the potential role of a European cross border adjustment mechanism}, series = {Journal of Cleaner Production}, volume = {380}, journal = {Journal of Cleaner Production}, number = {Part 2, Art. Nr.:135040}, publisher = {Elsevier}, issn = {0959-6526}, doi = {10.1016/j.jclepro.2022.135040}, year = {2022}, abstract = {The European Union's aim to become climate neutral by 2050 necessitates ambitious efforts to reduce carbon emissions. Large reductions can be attained particularly in energy intensive sectors like iron and steel. In order to prevent the relocation of such industries outside the EU in the course of tightening environmental regulations, the establishment of a climate club jointly with other large emitters and alternatively the unilateral implementation of an international cross-border carbon tax mechanism are proposed. This article focuses on the latter option choosing the steel sector as an example. In particular, we investigate the financial conditions under which a European cross border mechanism is capable to protect hydrogen-based steel production routes employed in Europe against more polluting competition from abroad. By using a floor price model, we assess the competitiveness of different steel production routes in selected countries. We evaluate the climate friendliness of steel production on the basis of specific GHG emissions. In addition, we utilize an input-output price model. It enables us to assess impacts of rising cost of steel production on commodities using steel as intermediates. Our results raise concerns that a cross-border tax mechanism will not suffice to bring about competitiveness of hydrogen-based steel production in Europe because the cost tends to remain higher than the cost of steel production in e.g. China. Steel is a classic example for a good used mainly as intermediate for other products. Therefore, a cross-border tax mechanism for steel will increase the price of products produced in the EU that require steel as an input. This can in turn adversely affect competitiveness of these sectors. Hence, the effects of higher steel costs on European exports should be borne in mind and could require the cross-border adjustment mechanism to also subsidize exports.}, language = {en} }