@article{Kleefeld2021,
  author    = {Kleefeld, Andreas},
  title     = {The hot spots conjecture can be false: some numerical examples},
  series = {Advances in Computational Mathematics},
  volume    = {47},
  journal   = {Advances in Computational Mathematics},
  publisher = {Springer},
  address   = {Dordrecht},
  issn      = {1019-7168},
  doi       = {10.1007/s10444-021-09911-5},
  year      = {2021},
  abstract  = {The hot spots conjecture is only known to be true for special geometries. This paper shows numerically that the hot spots conjecture can fail to be true for easy to construct bounded domains with one hole. The underlying eigenvalue problem for the Laplace equation with Neumann boundary condition is solved with boundary integral equations yielding a non-linear eigenvalue problem. Its discretization via the boundary element collocation method in combination with the algorithm by Beyn yields highly accurate results both for the first non-zero eigenvalue and its corresponding eigenfunction which is due to superconvergence. Additionally, it can be shown numerically that the ratio between the maximal/minimal value inside the domain and its maximal/minimal value on the boundary can be larger than 1 + 10- 3. Finally, numerical examples for easy to construct domains with up to five holes are provided which fail the hot spots conjecture as well.},
  language  = {en}
}
@article{DitzhausGaigall2018,
  author    = {Ditzhaus, Marc and Gaigall, Daniel},
  title     = {A consistent goodness-of-fit test for huge dimensional and functional data},
  series = {Journal of Nonparametric Statistics},
  volume    = {30},
  journal   = {Journal of Nonparametric Statistics},
  number    = {4},
  publisher = {Taylor \& Francis},
  address   = {Abingdon},
  issn      = {1029-0311},
  doi       = {10.1080/10485252.2018.1486402},
  pages     = {834 -- 859},
  year      = {2018},
  abstract  = {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 Cram{\´e}r-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.},
  language  = {en}
}
@article{HarrisKleefeld2022,
  author    = {Harris, Isaac and Kleefeld, Andreas},
  title     = {Analysis and computation of the transmission eigenvalues with a conductive boundary condition},
  series = {Applicable Analysis},
  volume    = {101},
  journal   = {Applicable Analysis},
  number    = {6},
  publisher = {Taylor \& Francis},
  address   = {London},
  issn      = {1563-504X},
  doi       = {10.1080/00036811.2020.1789598},
  pages     = {1880 -- 1895},
  year      = {2022},
  abstract  = {We provide a new analytical and computational study of the transmission eigenvalues with a conductive boundary condition. These eigenvalues are derived from the scalar inverse scattering problem for an inhomogeneous material with a conductive boundary condition. The goal is to study how these eigenvalues depend on the material parameters in order to estimate the refractive index. The analytical questions we study are: deriving Faber-Krahn type lower bounds, the discreteness and limiting behavior of the transmission eigenvalues as the conductivity tends to infinity for a sign changing contrast. We also provide a numerical study of a new boundary integral equation for computing the eigenvalues. Lastly, using the limiting behavior we will numerically estimate the refractive index from the eigenvalues provided the conductivity is sufficiently large but unknown.},
  language  = {en}
}
@article{ClausnitzerKleefeld2024,
  author    = {Clausnitzer, Julian and Kleefeld, Andreas},
  title     = {A spectral Galerkin exponential Euler time-stepping scheme for parabolic SPDEs on two-dimensional domains with a C² boundary},
  series = {Discrete and Continuous Dynamical Systems - Series B},
  volume    = {29},
  journal   = {Discrete and Continuous Dynamical Systems - Series B},
  number    = {4},
  publisher = {AIMS},
  address   = {Springfield},
  issn      = {1531-3492},
  doi       = {10.3934/dcdsb.2023148},
  pages     = {1624 -- 1651},
  year      = {2024},
  abstract  = {We consider the numerical approximation of second-order semi-linear parabolic stochastic partial differential equations interpreted in the mild sense which we solve on general two-dimensional domains with a C² boundary with homogeneous Dirichlet boundary conditions. The equations are driven by Gaussian additive noise, and several Lipschitz-like conditions are imposed on the nonlinear function. We discretize in space with a spectral Galerkin method and in time using an explicit Euler-like scheme. For irregular shapes, the necessary Dirichlet eigenvalues and eigenfunctions are obtained from a boundary integral equation method. This yields a nonlinear eigenvalue problem, which is discretized using a boundary element collocation method and is solved with the Beyn contour integral algorithm. We present an error analysis as well as numerical results on an exemplary asymmetric shape, and point out limitations of the approach.},
  language  = {en}
}
@article{AyalaHarrisKleefeld2024,
  author    = {Ayala, Rafael Ceja and Harris, Isaac and Kleefeld, Andreas},
  title     = {Direct sampling method via Landweber iteration for an absorbing scatterer with a conductive boundary},
  series = {Inverse Problems and Imaging},
  volume    = {18},
  journal   = {Inverse Problems and Imaging},
  number    = {3},
  publisher = {AIMS},
  address   = {Springfield},
  issn      = {1930-8337},
  doi       = {10.3934/ipi.2023051},
  pages     = {708 -- 729},
  year      = {2024},
  abstract  = {In this paper, we consider the inverse shape problem of recovering isotropic scatterers with a conductive boundary condition. Here, we assume that the measured far-field data is known at a fixed wave number. Motivated by recent work, we study a new direct sampling indicator based on the Landweber iteration and the factorization method. Therefore, we prove the connection between these reconstruction methods. The method studied here falls under the category of qualitative reconstruction methods where an imaging function is used to recover the absorbing scatterer. We prove stability of our new imaging function as well as derive a discrepancy principle for recovering the regularization parameter. The theoretical results are verified with numerical examples to show how the reconstruction performs by the new Landweber direct sampling method.},
  language  = {en}
}
@article{BaringhausGaigall2017,
  author    = {Baringhaus, Ludwig and Gaigall, Daniel},
  title     = {Hotelling's T² tests in paired and independent survey samples: An efficiency comparison},
  series = {Journal of Multivariate Analysis},
  volume    = {2017},
  journal   = {Journal of Multivariate Analysis},
  number    = {154},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0047-259X},
  doi       = {10.1016/j.jmva.2016.11.004},
  pages     = {177 -- 198},
  year      = {2017},
  abstract  = {Hotelling's T² tests in paired and independent survey samples are compared using the traditional asymptotic efficiency concepts of Hodges-Lehmann, Bahadur and Pitman, as well as through criteria based on the volumes of corresponding confidence regions. Conditions characterizing the superiority of a procedure are given in terms of population canonical correlation type coefficients. Statistical tests for checking these conditions are developed. Test statistics based on the eigenvalues of a symmetrized sample cross-covariance matrix are suggested, as well as test statistics based on sample canonical correlation type coefficients.},
  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{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{HarrisKleefeld2018,
  author    = {Harris, Isaac and Kleefeld, Andreas},
  title     = {The inverse scattering problem for a conductive boundary condition and transmission eigenvalues},
  series = {Applicable Analysis},
  volume    = {99},
  journal   = {Applicable Analysis},
  number    = {3},
  publisher = {Taylor \& Francis},
  address   = {London},
  issn      = {1563-504X},
  doi       = {10.1080/00036811.2018.1504028},
  pages     = {508 -- 529},
  year      = {2018},
  abstract  = {In this paper, we consider the inverse scattering problem associated with an inhomogeneous media with a conductive boundary. In particular, we are interested in two problems that arise from this inverse problem: the inverse conductivity problem and the corresponding interior transmission eigenvalue problem. The inverse conductivity problem is to recover the conductive boundary parameter from the measured scattering data. We prove that the measured scatted data uniquely determine the conductivity parameter as well as describe a direct algorithm to recover the conductivity. The interior transmission eigenvalue problem is an eigenvalue problem associated with the inverse scattering of such materials. We investigate the convergence of the eigenvalues as the conductivity parameter tends to zero as well as prove existence and discreteness for the case of an absorbing media. Lastly, several numerical and analytical results support the theory and we show that the inside-outside duality method can be used to reconstruct the interior conductive eigenvalues.},
  language  = {en}
}
@article{Gaigall2019,
  author    = {Gaigall, Daniel},
  title     = {On a new approach to the multi-sample goodness-of-fit problem},
  series = {Communications in Statistics - Simulation and Computation},
  volume    = {53},
  journal   = {Communications in Statistics - Simulation and Computation},
  number    = {10},
  publisher = {Taylor \& Francis},
  address   = {London},
  issn      = {1532-4141},
  doi       = {10.1080/03610918.2019.1618472},
  pages     = {2971 -- 2989},
  year      = {2019},
  abstract  = {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.},
  language  = {en}
}