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Related papers: On the meaning of mean shape

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We study the problem of conditional two-sample testing, which aims to determine whether two populations have the same distribution after accounting for confounding factors. This problem commonly arises in various applications, such as…

Machine Learning · Statistics 2026-05-05 Seongchan Lee , Suman Cha , Ilmun Kim

In this paper after a brief revision of VW-means, which are extrinsic means on real and complex projective spaces, relative to the Veronese-Whitney embeddings, we give two examples of sample VW means computations on planar Kendall shape…

Other Statistics · Statistics 2018-10-17 Yunfan Wang , Vic Patrangenaru

The sample median is often used in statistical analyses of physical or astronomical data wherein a central value must be found from samples polluted by elements which do not belong to the population of interest or when the underlying…

Data Analysis, Statistics and Probability · Physics 2008-04-04 Jean-Michel Levy

If $\Lambda $ is a measure space, $u:\Lambda ^{m}\rightarrow \Bbb{R}$ is a given function and $N\geq m,$ the function $U(x_{1},...,x_{N})=\left( \begin{array}{l} N \\ m \end{array} \right) ^{-1}\sum_{1\leq i_{1}<\cdots <i_{m}\leq…

Functional Analysis · Mathematics 2015-01-14 Irina Navrotskaya , Patrick J. Rabier

We endeavour to estimate numerous multi-dimensional means of various probability distributions on a common space based on independent samples. Our approach involves forming estimators through convex combinations of empirical means derived…

Machine Learning · Statistics 2025-03-11 Gilles Blanchard , Jean-Baptiste Fermanian , Hannah Marienwald

Size distortion can occur if an asymptotic testing procedure requiring diverging sample sizes, is implemented to data with very small sample sizes. In this paper, we consider one-sample and two-sample tests for mean vectors when data are…

Methodology · Statistics 2022-03-17 Jun Li

We consider a generalization of the hyperplane problem to arbitrary measures in place of volume and to sections of lower dimensions. We prove this generalization for unconditional convex bodies and for duals of bodies with bounded volume…

Metric Geometry · Mathematics 2015-03-24 Alexander Koldobsky

We develop a Morse-Lusternik-Schnirelmann theory for the distance between two points of a smoothly embedded circle in a complete Riemannian manifold. This theory suggests very naturally a definition of width that generalises the classical…

Differential Geometry · Mathematics 2025-03-27 Lucas Ambrozio , Rafael Montezuma , Roney Santos

The problem of estimating, from a random sample of points, the dimension of a compact subset $S$ of the Euclidean space is considered. The emphasis is put on consistency results in the statistical sense. That is, statements of convergence…

Statistics Theory · Mathematics 2025-07-08 Alejandro Cholaquidis , Antonio Cuevas , Beatriz Pateiro-López

In Euclidean space, the asymptotic shape of large cells in various types of Poisson driven random tessellations has been the subject of a famous conjecture due to David Kendall. Since shape is a geometric concept and large cells are…

Probability · Mathematics 2025-09-01 Daniel Hug , Andreas Reichenbacher

We construct examples of compact and one-ended constant mean curvature surfaces with large mean curvature in Riemannian manifolds with axial symmetry by gluing together small spheres positioned end-to-end along a geodesic. Such surfaces…

Differential Geometry · Mathematics 2008-12-17 Adrian Butscher , Rafe Mazzeo

We investigate connections between pairs of (pseudo-)Riemannian metrics whose sum is a (tensor) product of a covector field with itself. A bijective mapping between the classes of Euclidean and Lorentzian metrics is constructed as a special…

General Relativity and Quantum Cosmology · Physics 2007-05-23 Bozhidar Z. Iliev

We consider the numbers of positive and negative eigenvalues of matrices of squared distances between randomly sampled i.i.d. points in a given metric measure space. These numbers and their limits, as the number of points grows, in fact…

Metric Geometry · Mathematics 2025-08-12 Alexey Kroshnin , Tianyu Ma , Eugene Stepanov

We show that the positive mass theorem holds for continuous Riemannian metrics that lie in the Sobolev space $W^{2, n/2}_{loc}$ for manifolds of dimension less than or equal to $7$ or spin-manifolds of any dimension. More generally, we give…

Differential Geometry · Mathematics 2014-08-28 James D. E. Grant , Nathalie Tassotti

A mid-point theorem is proved in an elementary way for the U type shape of functions that arise out of exponential quadratic functions. These results are inspired from epidemic patterns and growth over a time period. Key words: natural…

Combinatorics · Mathematics 2021-06-15 Arni S. R. Srinivasa Rao

We study unimodular measures on the space $\mathcal M^d$ of all pointed Riemannian $d$-manifolds. Examples can be constructed from finite volume manifolds, from measured foliations with Riemannian leaves, and from invariant random subgroups…

Geometric Topology · Mathematics 2022-12-21 Miklos Abert , Ian Biringer

In this paper we prove two theorems. The first one is a structure result that describes the extrinsic geometry of an embedded surface with constant mean curvature (possibly zero) in a homogeneously regular Riemannian three-manifold, in any…

Differential Geometry · Mathematics 2014-01-10 William H. Meeks , Joaquín Pérez , Antonio Ros

Let $(M, {g})$ be a compact, $d$-dimensional Riemannian manifold without boundary. Suppose further that $(M,g)$ is either two dimensional and has no conjugate points or $(M,g)$ has non-positive sectional curvature. The goal of this note is…

Spectral Theory · Mathematics 2015-03-23 Kamil Mroz , Alexander Strohmaier

In the first part of this paper we prove some new Poincar\'e inequalities, with explicit constants, for domains of any hypersurface of a Riemannian manifold with sectional curvatures bounded from above. This inequalities involve the first…

Differential Geometry · Mathematics 2017-08-30 Hilário Alencar , Gregório Silva Neto

We propose a two-sample test for high-dimensional means that requires neither distributional nor correlational assumptions, besides some weak conditions on the moments and tail properties of the elements in the random vectors. This…

Methodology · Statistics 2019-04-17 Kaijie Xue , Fang Yao
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