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The cut polytope ${\rm CUT}(n)$ is the convex hull of the cut vectors in a complete graph with vertex set $\{1,\ldots,n\}$. It is well known in the area of combinatorial optimization and recently has also been studied in a direct relation…

Discrete Mathematics · Computer Science 2018-12-11 Nevena Maric

We establish central limit theorems for natural volumes of random inscribed polytopes in projective Riemannian or Finsler geometries. In addition, normal approximation of dual volumes and the mean width of random polyhedral sets are…

Metric Geometry · Mathematics 2020-05-22 Florian Besau , Daniel Rosen , Christoph Thäle

When testing for the mean vector in a high dimensional setting, it is generally assumed that the observations are independently and identically distributed. However if the data are dependent, the existing test procedures fail to preserve…

Statistics Theory · Mathematics 2014-11-17 Deepak Nag Ayyala , Junyong Park , Anindya Roy

The goal of any estimation study is an interval estimation of a the parameter(s) of interest. These estimations are mostly expressed using empirical confidence intervals that are based on sample point estimates of the corresponding…

Methodology · Statistics 2018-07-03 Ilya Novikov

Following S\"odergren, we consider a collection of random variables on the space $X_n$ of unimodular lattices in dimension $n$: Normalizations of the angles between the $N = N(n)$ shortest vectors in a random unimodular lattice, and the…

Number Theory · Mathematics 2022-06-15 Kristian Holm

This paper investigates the minimum mean square error (MMSE) estimation of x, given the observation y = Hx+n, when x and n are independent and Gaussian Mixture (GM) distributed. The introduction of GM distributions, represents a…

Statistics Theory · Mathematics 2011-08-18 John T. Flam , Saikat Chatterjee , Kimmo Kansanen , Torbjorn Ekman

We study the regularity of densities of distributions that are polynomial images of the standard Gaussian measure on $\mathbb{R}^n$. We assume that the degree of a polynomial is fixed and that each variable enters to a power bounded by…

Probability · Mathematics 2020-07-28 Egor Kosov

The bivariate normal density with unit variance and correlation $\rho$ is well-known. We show that by integrating out $\rho$, the result is a function of the maximum norm. The Bayesian interpretation of this result is that if we put a…

Statistics Theory · Mathematics 2015-11-20 Kai Zhang , Lawrence D. Brown , Edward George , Linda Zhao

We find a two term asymptotic expansion for the optimal expected value of a sequentially selected monotone subsequence from a random permutation of length n. A striking feature of this expansion is that tells us that the expected value of…

Probability · Mathematics 2015-09-16 Peichao Peng , J. Michael Steele

This paper gives upper and lower bounds on the gap in Jensen's inequality, i.e., the difference between the expected value of a function of a random variable and the value of the function at the expected value of the random variable. The…

Probability · Mathematics 2020-08-21 Xiang Gao , Meera Sitharam , Adrian E. Roitberg

Random planar graphs have been the subject of much recent work. Many basic properties of the standard uniform random planar graph P_{n}, by which we mean a graph chosen uniformly at random from the set of all planar graphs with vertex set…

Combinatorics · Mathematics 2013-07-23 Chris Dowden

We prove a limit theorem for the the maximal interpoint distance (also called the diameter) for a sample of n i.i.d. points in the unit ball of dimension 2 or more. The exact form of the limit distribution and the required normalisation are…

Probability · Mathematics 2007-05-23 Michael Mayer , Ilya Molchanov

The empirical mean of $n$ independent and identically distributed (i.i.d.) random variables $(X_1,\dots,X_n)$ can be viewed as a suitably normalized scalar projection of the $n$-dimensional random vector $X^{(n)}\doteq(X_1,\dots,X_n)$ in…

Probability · Mathematics 2015-10-07 Nina Gantert , Steven Soojin Kim , Kavita Ramanan

Given an m-dimensional compact submanifold $\mathbf{M}$ of Euclidean space $\mathbf{R}^s$, the concept of mean location of a distribution, related to mean or expected vector, is generalized to more general $\mathbf{R}^s$-valued functionals…

Statistics Theory · Mathematics 2007-08-07 Harrie Hendriks , Zinoviy Landsman

Constructing distribution-free confidence intervals for the median, a classic problem in statistics, has seen numerous solutions in the literature. While coverage validity has received ample attention, less has been explored about interval…

Statistics Theory · Mathematics 2024-03-12 Manit Paul , Arun Kumar Kuchibhotla

We provide an asymptotic expansion of the maximal mean squared error (MSE) of the sample median to be attained on shrinking gross error neighborhoods about an ideal central distribution. More specifically, this expansion comes in powers of…

Statistics Theory · Mathematics 2010-06-02 Peter Ruckdeschel

We study frequentist risk properties of predictive density estimators for mean mixtures of multivariate normal distributions, involving an unknown location parameter $\theta \in \mathbb{R}^d$, and which include multivariate skew normal…

Statistics Theory · Mathematics 2022-02-02 Pankaj Bhagwat , Eric Marchand

We propose a summary measure defined as the expected value of a random variable over disjoint subsets of its support that are specified by a given grid of proportions, and consider its use in a regression modeling framework. The obtained…

Statistics Theory · Mathematics 2018-10-19 Celia García-Pareja , Matteo Bottai

We extend a recently established asymptotic normality theorem for generalized linear mixed models to include the dispersion parameter. The new results show that the maximum likelihood estimators of all model parameters have asymptotically…

Statistics Theory · Mathematics 2022-08-11 Aishwarya Bhaskaran , Matt P. Wand

We show that the number of cycles in a random permutation chosen according to generalized Ewens measure is normally distributed and compute asymptotic estimates for the mean and variance.

Probability · Mathematics 2013-08-16 Kenneth Maples , Ashkan Nikeghbali , Dirk Zeindler