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We present a new algorithm for Tukey (halfspace) depth level sets and its implementation. Given $d$-dimensional data set for any $d\geq 2$, the algorithm is based on representation of level sets as intersections of balls in $R^d$, and can…

Computational Geometry · Computer Science 2016-11-16 Milica Bogicevic , Milan Merkle

Notions of depth in regression have been introduced and studied in the literature. Regression depth (RD) of Rousseeuw and Hubert (1999), the most famous one, is a direct extension of Tukey location depth (Tukey (1975)) to regression. Like…

Statistics Theory · Mathematics 2020-07-13 Yijun Zuo

Tukey depth regions are important notions in nonparametric multivariate data analysis. A $\tau$-th Tukey depth region $\mathcal{D}_{\tau}$ is the set of all points that have at least depth $\tau$. While the Tukey depth regions are easily…

Computation · Statistics 2014-04-17 Xiaohui Liu

We consider a common measurement paradigm, where an unknown subset of an affine space is measured by unknown continuous quasi-convex functions. Given the measurement data, can one determine the dimension of this space? In this paper, we…

Algebraic Topology · Mathematics 2020-07-08 Min-Chun Wu , Vladimir Itskov

This paper studies how to generalize Tukey's depth to problems defined in a restricted space that may be curved or have boundaries, and to problems with a nondifferentiable objective. First, using a manifold approach, we propose a broad…

Methodology · Statistics 2023-05-05 Yiyuan She , Shao Tang , Jingze Liu

We develop a novel exploratory tool for non-Euclidean object data based on data depth, extending the celebrated Tukey's depth for Euclidean data. The proposed metric halfspace depth, applicable to data objects in a general metric space,…

Methodology · Statistics 2021-09-02 Xiongtao Dai , Sara Lopez-Pintado

We study the pointwise dimension for a new class of projection measures on arbitrary fractal limit sets without separation conditions. We prove that the pointwise dimension exists a.e. for this class of measures associated to equilibrium…

Dynamical Systems · Mathematics 2019-08-28 Eugen Mihailescu

Phantom depth, phantom nonzerodivisors, and phantom exact sequences are analogues of the non-"phantom" notions which have been useful in tackling the (very difficult) localization problem in tight closure theory. In the present paper, these…

Commutative Algebra · Mathematics 2010-02-26 Neil M. Epstein

Given a Radon probability measure $\mu$ supported in $\mathbb{R}^d$, we are interested in those points $x$ around which the measure is concentrated infinitely many times on thin annuli centered at $x$. Depending on the lower and upper…

Classical Analysis and ODEs · Mathematics 2022-08-26 Zoltán Buczolich , Stéphane Seuret

Reay's relaxed Tverberg conjecture and Conway's thrackle conjecture are open problems about the geometry of pairwise intersections. Reay asked for the minimum number of points in Euclidean d-space that guarantees any such point set admits a…

\We introduce the horospherical depth, an intrinsic notion of statistical depth on Hadamard manifolds, and define the Busemann median as the set of its maximizers. The construction exploits the fact that the linear functionals appearing in…

Statistics Theory · Mathematics 2026-05-14 Yangdi Jiang , Xiaotian Chang , Cyrus Mostajeran

We introduce the notion of tubular dimension, and give a formula for it. As an application we show that every invariant measure of a $C^{1+\gamma}$ diffeomorphism of a closed Riemannian manifold admits an asymptotic local product structure…

Dynamical Systems · Mathematics 2024-02-13 Snir Ben Ovadia

For any closed smooth Riemannian manifold H. Weyl has defined a sequence of numbers called today intrinsic volumes. They include volume, Euler characteristic, and integral of the scalar curvature. We conjecture that absolute values of all…

Differential Geometry · Mathematics 2017-11-16 Semyon Alesker

The Shapley-Folkman theorem shows that Minkowski averages of uniformly bounded sets tend to be convex when the number of terms in the sum becomes much larger than the ambient dimension. In optimization, Aubin and Ekeland [1976] show that…

Optimization and Control · Mathematics 2019-07-02 Thomas Kerdreux , Igor Colin , Alexandre d'Aspremont

Tukey depth function is one of the most famous multivariate tools serving robust purposes. It is also very well known for its computability problems in dimensions $p \ge 3$. In this paper, we address this computing issue by presenting two…

Computation · Statistics 2016-10-07 Xiaohui Liu

The notion of metric entropy dimension is introduced to measure the complexity of entropy zero dynamical systems. For measure preserving systems, we define entropy dimension via the dimension of entropy generating sequences. This…

Dynamical Systems · Mathematics 2018-02-27 Dou Dou , Wen Huang , Kyewon Koh Park

We study empirical variants of the halfspace (Tukey) depth of a probability measure $\mu$, which are obtained by replacing $\mu$ with the corresponding weighted empirical measure. We prove analogues of the Marcinkiewicz--Zygmund strong law…

Probability · Mathematics 2024-03-15 Andrii Ilienko , Ilya Molchanov , Riccardo Turin

We investigate some properties of density measures -- finitely additive measures on the set of natural numbers $\N$ extending asymptotic density. We introduce a class of density measures, which is defined using cluster points of the…

Number Theory · Mathematics 2013-05-31 Martin Sleziak , Miloš Ziman

Little known relations of the renown concept of the halfspace depth for multivariate data with notions from convex and affine geometry are discussed. Halfspace depth may be regarded as a measure of symmetry for random vectors. As such, the…

Statistics Theory · Mathematics 2022-09-26 Stanislav Nagy , Carsten Schuett , Elisabeth M. Werner

We develop a new method to estimate the area, and more generally the intrinsic volumes, of a compact subset $X$ of $\mathbb{R}^d$ from a set $Y$ that is close in the Hausdorff distance. This estimator enjoys a linear rate of convergence as…

Metric Geometry · Mathematics 2024-07-22 David Cohen-Steiner , Antoine Commaret