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A Chebyshev-type quadrature for a given weight function is a quadrature formula with equal weights. In this work we show that a method presented by Kane may be used to produce tight bounds for the minimal number of nodes required in…

Classical Analysis and ODEs · Mathematics 2017-06-20 Shoni Gilboa , Ron Peled

In this paper, we derive new probability bounds for Chebyshev's inequality if the supremum of the probability density function is known. This result holds for one-dimensional or multivariate continuous probability distributions with finite…

Methodology · Statistics 2019-02-12 Tomohiro Nishiyama

We consider the computation of quadrature rules that are exact for a Chebyshev set of linearly independent functions on an interval $[a,b]$. A general theory of Chebyshev sets guarantees the existence of rules with a Gaussian property, in…

Numerical Analysis · Mathematics 2017-11-01 Daan Huybrechs

We study the problem of approximately recovering a probability distribution given noisy measurements of its Chebyshev polynomial moments. This problem arises broadly across algorithms, statistics, and machine learning. By leveraging a…

Data Structures and Algorithms · Computer Science 2026-05-20 Cameron Musco , Christopher Musco , Lucas Rosenblatt , Apoorv Vikram Singh

We give Chebyshev-type quadrature formulas for certain new weight classes. These formulas are of highest possible degree when the number of nodes is a power of 2. We also describe the nodes in a constructive way, which is important for…

Numerical Analysis · Mathematics 2011-11-15 Armen Vagharshakyan

We consider the problem of estimating the support size of a discrete distribution whose minimum non-zero mass is at least $ \frac{1}{k}$. Under the independent sampling model, we show that the sample complexity, i.e., the minimal sample…

Statistics Theory · Mathematics 2016-12-13 Yihong Wu , Pengkun Yang

We prove results on existence of limits in the definition of (weighted) directional Chebyshev constants at all points of the standard simplex $\Sigma \subset {\bf R}^d$ for (locally) regular compact sets $K\subset {\bf C}^d$.

Complex Variables · Mathematics 2024-08-15 Thomas Bloom , Norman Levenberg

Due to their importance in both data analysis and numerical algorithms, low rank approximations have recently been widely studied. They enable the handling of very large matrices. Tight error bounds for the computationally efficient…

Numerical Analysis · Mathematics 2023-04-06 Frank de Hoog , Markus Hegland

Let $d$ and $k$ be positive integers. Let $\mu$ be a positive Borel measure on $\mathbb{R}^2$ possessing finite moments up to degree $2d-1$. If the support of $\mu$ is contained in an algebraic curve of degree $k$, then we show that there…

Numerical Analysis · Mathematics 2017-10-31 Cordian Riener , Markus Schweighofer

Hypothesis testing is a fundamental issue in statistical inference and has been a crucial element in the development of information sciences. The Chernoff bound gives the minimal Bayesian error probability when discriminating two hypotheses…

Quantum Physics · Physics 2009-11-13 J. Calsamiglia , R. Munoz-Tapia , Ll. Masanes , A. Acin , E. Bagan

This note concerns a somewhat innocent question motivated by an observation concerning the use of Chebyshev bounds on sample estimates of $p$ in the binomial distribution with parameters $n,p$. Namely, what moment order produces the best…

Probability · Mathematics 2017-11-21 Chris Jennings-Shaffer , Dane R. Skinner , Edward C. Waymire

Let $S_n^\lambda$ be the set of all permutations over the multiset $\{\overbrace{1,...,1}^{\lambda},...,\overbrace{m,...,m}^\lambda\}$ where $n=m\lambda$. A frequency permutation array (FPA) of minimum distance $d$ is a subset of…

Information Theory · Computer Science 2011-02-16 Min-Zheng Shieh , Shi-Chun Tsai

An explicit bound is given for the Kolmogorov distance between a mixture of normal distributions and a normal distribution with properly chosen parameter values. A random variable X has a mixture of normal distributions if its conditional…

Probability · Mathematics 2020-08-07 Krzysztof Bartoszek , Torkel Erhardsson

We provide explicit expressions for quadrature rules on the space of $C^1$ quintic splines with uniform knot sequences over finite domains. The quadrature nodes and weights are derived via an explicit recursion that avoids an intervention…

Numerical Analysis · Mathematics 2015-03-04 Michael Bartoň , Rachid Ait-Haddou , Victor Manuel Calo

We establish quantitative bounds for rates of convergence and asymptotic variances for iterated conditional sequential Monte Carlo (i-cSMC) Markov chains and associated particle Gibbs samplers. Our main findings are that the essential…

Probability · Mathematics 2015-04-15 Christophe Andrieu , Anthony Lee , Matti Vihola

In this paper, we study the optimal general convergence rates for quadratures derived from Chebyshev points. By building on the aliasing errors on integration of Chebyshev polynomials, together with the asymptotic formulae on the…

Numerical Analysis · Mathematics 2014-07-29 Shuhuang Xiang

Sectional curvature bounds are of central importance in the study of Riemannian manifolds, both in smooth differential geometry and in the generalized synthetic setting of Alexandrov spaces. Riemannian metrics along with metric spaces of…

Differential Geometry · Mathematics 2026-01-30 Darius Erös , Michael Kunzinger , Argam Ohanyan , Alessio Vardabasso

The paper deals with a special filtered approximation method, which originates interpolation polynomials at Chebyshev zeros by using de la Vall\'ee Poussin filters. These polynomials can be an useful device for many theoretical and…

Numerical Analysis · Mathematics 2020-08-04 Donatella Occorsio , Woula Themistoclakis

The theory of Chebyshev (uniform) approximation for univariate polynomial and piecewise polynomial functions has been studied for decades. The optimality conditions are based on the notion of alternating sequence. However, the extension the…

Numerical Analysis · Mathematics 2017-09-01 Nadezda Sukhorukova , Julien Ugon , David Yost

For a fixed number field $K$, we consider the mean square error in estimating the number of primes with norm congruent to $a$ modulo $q$ by the Chebotar\"ev Density Theorem when averaging over all $q\le Q$ and all appropriate $a$. Using a…

Number Theory · Mathematics 2012-10-16 Ethan Smith
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