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We introduce a new class of (not necessarily convex) bodies and show, among other things, that these bodies provide yet another link between convex geometric analysis and information theory. Namely, they give geometric interpretations of…

Functional Analysis · Mathematics 2011-05-17 Justin Jenkinson , Elisabeth Werner

An identity due to Efron dating from 1965 relates the expected volume of the convex hull of $n$ random points to the expected number of vertices of the convex hull of $n+1$ random points. Forty years later this identity was extended from…

Probability · Mathematics 2022-10-04 Christian Buchta

We prove an exponential deviation inequality for the convex hull of a finite sample of i.i.d. random points with a density supported on an arbitrary convex body in $\R^d$, $d\geq 2$. When the density is uniform, our result yields rate…

Probability · Mathematics 2017-04-07 Victor-Emmanuel Brunel

A probabilistic representation for a class of weighted $p$-radial distributions, based on mixtures of a weighted cone probability measure and a weighted uniform distribution on the Euclidean $\ell_p^n$-ball, is derived. Large deviation…

Probability · Mathematics 2022-06-01 Tom Kaufmann , Christoph Thaele

Consider a pair of cumulative distribution functions $F$ and $G$, where $F$ is unknown and $G$ is a known reference distribution. Given a sample from $F$, we propose tests to detect the convexity or the concavity of $G^{-1}\circ F$ versus…

Statistics Theory · Mathematics 2025-06-25 Tommaso Lando , Mohammed Es-Salih Benjrada

A full-rank lattice in the Euclidean space is a discrete set formed by all integer linear combinations of a basis. Given a probability distribution on $\mathbb{R}^n$, two operations can be induced by considering the quotient of the space by…

Information Theory · Computer Science 2024-05-15 Fábio C. C. Meneghetti , Henrique K. Miyamoto , Sueli I. R. Costa

Motivated by a problem on the 67th William Lowell Putnam Mathematical Competition, we will summarize three different solutions found on a website. This Putman problem is a special case of Sylvester's four point problem! Suppose four points…

Metric Geometry · Mathematics 2021-09-14 Sheree Sharpe

The assessment of laboratory animal behavior is of central interest in modern neuroscience research. Behavior is typically studied in terms of pose changes, which are ideally captured in three dimensions. This requires triangulation over a…

Computer Vision and Pattern Recognition · Computer Science 2021-06-25 Indrani Sarkar , Indranil Maji , Charitha Omprakash , Sebastian Stober , Sanja Mikulovic , Pavol Bauer

Spaces of convex and concave functions appear naturally in theory and applications. For example, convex regression and log-concave density estimation are important topics in nonparametric statistics. In stochastic portfolio theory, concave…

Probability · Mathematics 2021-05-25 Peter Baxendale , Ting-Kam Leonard Wong

We study volumes of sections of convex origin-symmetric bodies in $\mathbb{R}% ^{n}$ induced by orthonormal systems on probability spaces. The approach is based on volume estimates of \ John-L\"{o}wner ellipsoids and expectations of norms…

Functional Analysis · Mathematics 2022-12-08 Alexander Kushpel

We consider the family of convex bodies obtained from an origin symmetric convex body $K$ by multiplication with diagonal matrices, by forming Minkowski sums of the transformed sets, and by taking limits in the Hausdorff metric. Support…

Metric Geometry · Mathematics 2019-09-10 Ilya Molchanov , Felix Nagel

We study the geometry of centrally-symmetric random polytopes, generated by $N$ independent copies of a random vector $X$ taking values in $\mathbb{R}^n$. We show that under minimal assumptions on $X$, for $N \gtrsim n$ and with high…

Probability · Mathematics 2019-07-18 Olivier Guédon , Felix Krahmer , Christian Kümmerle , Shahar Mendelson , Holger Rauhut

Several general trends have been identified for equilibrated, self-gravitating collisionless systems, such as density or anisotropy profiles. These are integrated quantities which naturally depend on the underlying velocity distribution…

Astrophysics · Physics 2009-11-11 Steen H. Hansen , Ben Moore , Marcel Zemp , Joachim Stadel

The intrinsic volumes of a convex body are fundamental invariants that capture information about the average volume of the projection of the convex body onto a random subspace of fixed dimension. The intrinsic volumes also play a central…

Metric Geometry · Mathematics 2022-08-31 Martin Lotz , Joel A. Tropp

A new class of distributional transformations is introduced, characterized by equations relating function weighted expectations of test functions on a given distribution to expectations of the transformed distribution on the test function's…

Probability · Mathematics 2007-05-23 Larry Goldstein , Gesine Reinert

We consider an even probability distribution on the $d$-dimensional Euclidean space with the property that it assigns measure zero to any hyperplane through the origin. Given $N$ independent random vectors with this distribution, under the…

Probability · Mathematics 2020-12-24 Daniel Hug , Rolf Schneider

Consider some convex body $K\subset\mathbb R^d$. Let $X_1,\dots, X_k$, where $k\leq d$, be random points independently and uniformly chosen in $K$, and let $\xi_k$ be a uniformly distributed random linear $k$-plane. We show that for…

Metric Geometry · Mathematics 2022-02-08 Alexander E. Litvak , Dmitry Zaporozhets

We consider the scattering by a one-dimensional random potential and derive the probability distribution of the corresponding Wigner time delay. It is shown that the limiting distribution is the same for two different models and coincides…

Disordered Systems and Neural Networks · Physics 2009-10-30 Alain Comtet , Christophe Texier

A simple numerical method for loading of a relativistic Maxwellian-type distribution is proposed based on inverse transform sampling. The relativistic Maxwellian energy distribution is introduced as an alternative to the Maxwell-J\"{u}ttner…

Plasma Physics · Physics 2026-03-05 Takayuki Umeda

Chance constraints describe a set of given random inequalities depending on the decision vector satisfied with a large enough probability. They are widely used in decision making under uncertain data in many engineering problems. This paper…

Optimization and Control · Mathematics 2025-04-01 Heng Zhang , Abdel Lisser