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Related papers: $L_p$-norm spherical copulas

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We prove certain $L^p$ estimates ($1<p<\infty$) for non-isotropic singular integrals along surfaces of revolution. As an application we obtain $L^p$ boundedness of the singular integrals under a sharp size condition on their kernels.

Classical Analysis and ODEs · Mathematics 2008-09-22 Shuichi Sato

Upper bounds for the $L_p$-discrepancies of point distributions in compact metric measure spaces for $0<p\le\infty$ have been established in the paper [6] by Brandolini, Chen, Colzani, Gigante and Travaglini. In the present paper we show…

Metric Geometry · Mathematics 2018-05-01 M. M. Skriganov

This paper studies the relationship between volume and surface uniform measures on n-dimensional p-balls under the p-norm. It is proved that for p=1, p=2 and p=infinity, and only for these values of p, radial projection maps a…

Statistics Theory · Mathematics 2025-11-20 Carlos Pinzón

We study the $L_p$-discrepancy of random point sets in high dimensions, with emphasis on small values of $p$. Although the classical $L_p$-discrepancy suffers from the curse of dimensionality for all $p \in (1,\infty)$, the gap between…

Numerical Analysis · Mathematics 2025-12-10 Erich Novak , Friedrich Pillichshammer

Motivated by the definition of the Gowers uniformity norms, we introduce and study a wide class of norms. Our aim is to establish them as a natural generalization of the $L_p$ norms. We shall prove that these normed spaces share many of the…

Combinatorics · Mathematics 2009-03-20 Hamed Hatami

To any $n$-dimensional random vector $X$ we may associate its $L_p$-centroid body ${\cal Z}_p(X)$ and the corresponding norm. We formulate a conjecture concerning the bound on the ${\cal Z}_p(X)$-norm of $X$ and show that it holds under…

Probability · Mathematics 2020-10-27 Rafał Latała

We establish L^p bounds on L^2 normalized spectral clusters for self-adjoint elliptic Dirichlet forms with Lipschitz coefficients. In two dimensions we obtain best possible bounds for all p between $2 and infinity, up to logarithmic losses…

Analysis of PDEs · Mathematics 2012-07-11 Herbert Koch , Hart Smith , Daniel Tataru

Tractable generalizations of the Gaussian distribution play an important role for the analysis of high-dimensional data. One very general super-class of Normal distributions is the class of $\nu$-spherical distributions whose random…

Other Statistics · Statistics 2010-08-05 Fabian Sinz , Matthias Bethge

We consider inequalities between $L_p$-norms of partial derivatives, $p\in [1,+\infty]$, for bivariate concave functions on a convex domain that vanish on the boundary. Can the ratio between those norms be arbitrarily large? If not, what is…

Classical Analysis and ODEs · Mathematics 2025-05-06 Alexander Plakhov , Vladimir Protasov

We consider products of uniform random variables from the Stiefel manifold of orthonormal $k$-frames in $\mathbb{R}^n$, $k \le n$, and random vectors from the $n$-dimensional $\ell_p^n$-ball $\mathbb{B}_p^n$ with certain $p$-radial…

Probability · Mathematics 2022-03-02 Tom Kaufmann , Holger Sambale , Christoph Thäle

The aim of this article is to write the $p$-Wasserstein metric $W_p$ with the $p$-norm, $p\in [1,\infty)$, on $\R^d$ in terms of copula. In particular for the case of one-dimensional distributions, we get that the copula employed to get the…

Statistics Theory · Mathematics 2024-10-29 Mariem Abdellatif , Peter Kuching , Barbara Rüdiger , Irene Ventura

In this paper, we establish the $L^{p}(\mathbb{R}^{d})$-boundedness of the variation operator and the $\delta$-jump operator for generalized spherical means, and we also show the necessary conditions for the…

Classical Analysis and ODEs · Mathematics 2024-04-16 Wenjuan Li , Dongyong Yang , Feng Zhang

Copulas are known to satisfy a number of regularity properties, and one might therefore believe that their densities, when they exist, admit a certain degree of regularity themselves. We show that this is not true in general by constructing…

Probability · Mathematics 2022-04-12 Michaël Lalancette , Robert Zimmerman

We analyze the limit of the p-form Laplacian under a collapse, with bounded sectional curvature and bounded diameter, to a smooth limit space. As an application, we characterize when the p-form Laplacian has small positive eigenvalues in a…

Differential Geometry · Mathematics 2007-05-23 John Lott

Although copulas are used and defined for various infinite-dimensional objects (e.g. Gaussian processes and Markov processes), there is no prevalent notion of a copula that unifies these concepts. We propose a unified approach and define…

Probability · Mathematics 2020-12-23 Fred Espen Benth , Giulia Di Nunno , Dennis Schroers

We study $L^p\rightarrow L^q(V^r_E)$ variation semi-norm estimates for the spherical averaging operator, where $E\subset [1,2]$.

Classical Analysis and ODEs · Mathematics 2024-09-10 Reuben Wheeler

In this article, we study the fractional spherical maximal function and its lacunary counterpart. We study the necessary and sufficient conditions for $L^p-L^q$ boundedness of both maximal functions. In particular, we prove the restricted…

Analysis of PDEs · Mathematics 2026-04-29 Riju Basak , Surjeet Singh Choudhary , Daniel Spector

We consider $r$-variation operators for the family of spherical means, with special emphasis on $L^p\to L^q$ estimates.

Classical Analysis and ODEs · Mathematics 2021-10-26 David Beltran , Richard Oberlin , Luz Roncal , Andreas Seeger , Betsy Stovall

In dimension $n=1$ we obtain $L^{p_1}(\mathbb R) \times\dots\times L^{p_m}(\mathbb R)$ to $L^p(\mathbb R)$ boundedness for the multilinear spherical maximal function in the largest possible open set of indices and we provide counterexamples…

Classical Analysis and ODEs · Mathematics 2024-12-04 Georgios Dosidis , João P. G. Ramos

The study of high-dimensional distributions is of interest in probability theory, statistics and asymptotic convex geometry, where the object of interest is the uniform distribution on a convex set in high dimensions. The $\ell^p$ spaces…

Probability · Mathematics 2018-06-21 Steven Soojin Kim , Kavita Ramanan
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