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We prove the solvability in Sobolev spaces for both divergence and non-divergence form higher order parabolic and elliptic systems in the whole space, on a half space, and on a bounded domain. The leading coefficients are assumed to be…

Analysis of PDEs · Mathematics 2015-05-18 Hongjie Dong , Doyoon Kim

Covariance representations are developed for the uniform distributions on the Euclidean spheres in terms of spherical gradients and Hessians. They are applied to derive a number of Sobolev type inequalities and to recover and refine the…

Probability · Mathematics 2024-03-29 Sergey G. Bobkov , Devraj Duggal

Hyperuniformity characterizes a state of matter for which density fluctuations diminish towards zero at the largest length scales. However, the task of determining whether or not an experimental system is hyperuniform is experimentally…

Soft Condensed Matter · Physics 2015-06-22 Remi Dreyfus , Ye Xu , Tim Still , Lawrence A. Hough , A. G. Yodh , Salvatore Torquato

The nonrelativistic limit of a semilinear field equation is considered in a uniform and isotropic space.The scale-function of the space is constructed based on the Einstein equation.The Cauchy problem of the limit-equation is considered,and…

Mathematical Physics · Physics 2020-12-23 Makoto Nakamura

We develop tests for high-dimensional covariance matrices under a generalized elliptical model. Our tests are based on a central limit theorem (CLT) for linear spectral statistics of the sample covariance matrix based on self-normalized…

Statistics Theory · Mathematics 2019-12-17 Xinxin Yang , Xinghua Zheng , Jiaqi Chen

We consider linear models with scalar responses and covariates from a separable Hilbert space. The aim is to detect change points in the error distribution, based on sequential residual empirical distribution functions. Expansions for those…

Statistics Theory · Mathematics 2024-11-08 Natalie Neumeyer , Leonie Selk

We study a novel class of affine invariant and consistent tests for normality in any dimension. The tests are based on a characterization of the standard $d$-variate normal distribution as the unique solution of an initial value problem of…

Methodology · Statistics 2019-09-30 Philip Dörr , Bruno Ebner , Norbert Henze

Testing heteroscedasticity of the errors is a major challenge in high-dimensional regressions where the number of covariates is large compared to the sample size. Traditional procedures such as the White and the Breusch-Pagan tests…

Methodology · Statistics 2017-10-16 Zhaoyuan Li , Jianfeng Yao

This paper investigates instances of Sobolev embeddings characterized by local compactness at every point within their domain, except for a single point. We obtain the sharp conditions that distinguish compactness from non-compactness and…

Functional Analysis · Mathematics 2024-09-17 Chian Yeong Chuah , Jan Lang

We study the motion of an incompressible perfect liquid body in vacuum. This can be thought of as a model for the motion of the ocean or a star. The free surface moves with the velocity of the liquid and the pressure vanishes on the free…

Analysis of PDEs · Mathematics 2007-05-23 Hans Lindblad

We present an algorithm for testing halfspaces over arbitrary, unknown rotation-invariant distributions. Using $\tilde O(\sqrt{n}\epsilon^{-7})$ random examples of an unknown function $f$, the algorithm determines with high probability…

Data Structures and Algorithms · Computer Science 2018-11-02 Nathaniel Harms

Maximum Mean Discrepancy (MMD) has been widely used in the areas of machine learning and statistics to quantify the distance between two distributions in the $p$-dimensional Euclidean space. The asymptotic property of the sample MMD has…

Statistics Theory · Mathematics 2023-08-29 Hanjia Gao , Xiaofeng Shao

We find extremely general classes of nonsmooth open sets which guarantee Mosco convergence for corresponding Sobolev spaces and the validity of Sobolev inequalities with a uniform constant. An important feature of our results is that the…

Analysis of PDEs · Mathematics 2022-03-09 Matteo Fornoni , Luca Rondi

We propose three test criteria each of which is appropriate for testing, respectively, the equivalence hypotheses of symmetry, of homogeneity, and of independence, with multivariate data. All quantities have the common feature of involving…

Methodology · Statistics 2023-11-09 Feifei Chen , Simos G. Meintanis , Lixing Zhu

We consider N-tensor powers of a positive Hermitian line bundle L over a non-compact complex manifold X. In the compact case, B. Shiffman and S. Zelditch proved that the zeros of random sections become asymptotically uniformly distributed…

Complex Variables · Mathematics 2012-10-23 Tien-Cuong Dinh , George Marinescu , Viktoria Schmidt

A low frequency approximation of the discrete Sommerfeld diffraction problems, involving the scattering of a time harmonic lattice wave incident on square lattice by a discrete Dirichlet or a discrete Neumann half-plane, is investigated. It…

Analysis of PDEs · Mathematics 2019-08-08 Basant Lal Sharma

In this work, we revisit the problem of uniformity testing of discrete probability distributions. A fundamental problem in distribution testing, testing uniformity over a known domain has been addressed over a significant line of works, and…

Data Structures and Algorithms · Computer Science 2017-08-17 Tuğkan Batu , Clément L. Canonne

We consider two-dimensional hydroelastic waves, in which a free fluid surface separates two fluids of infinite vertical extent. Elastic effects are accounted for at the interface, with a parameter measuring the elastic bending force and…

Analysis of PDEs · Mathematics 2024-06-21 Shunlian Liu , David M. Ambrose

We consider the goodness-of-fit testing problem of distinguishing whether the data are drawn from a specified distribution, versus a composite alternative separated from the null in the total variation metric. In the discrete case, we…

Statistics Theory · Mathematics 2017-07-03 Sivaraman Balakrishnan , Larry Wasserman

We introduce nonparametric tests of independence for bivariate circular data based on trigonometric moments. Our contributions lie in (i) proposing nonparametric tests that are locally and asymptotically optimal against bivariate cosine von…