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We develop a computationally efficient and robust algorithm for generating pseudo-random samples from a broad class of smooth probability distributions in one and two dimensions. The algorithm is based on inverse transform sampling with a…

Numerical Analysis · Mathematics 2013-07-05 Sheehan Olver , Alex Townsend

We construct one and two parameter deformations of the two dimensional Chebyshev polynomials with simple recurrence coefficients, following the algorithm in [3]. Using inverse scattering techniques, we compute the corresponding…

Classical Analysis and ODEs · Mathematics 2012-09-20 Jeffrey S. Geronimo , Plamen Iliev

We consider the problem of approximating two, possibly unrelated probability distributions from a single complex-valued function $\psi$ and its Fourier transform. We show that this problem always has a solution within a specified degree of…

Mathematical Physics · Physics 2011-01-12 W. D. Flanders , G. Japaridze

In this paper we present the result of successively applying a Chebyshev polynomial to a continuous random variable. In particular we show that under mild assumptions the limiting distribution will be the same as the weight with respect to…

Numerical Analysis · Mathematics 2023-10-27 Javier Chico Vazquez , Andrew J. Horning

We present numerical solutions for differential equations by expanding the unknown function in terms of Chebyshev polynomials and solving a system of linear equations directly for the values of the function at the extrema (or zeros) of the…

Computational Physics · Physics 2009-10-31 Bogdan Mihaila , Ioana Mihaila

This article is concerned with an extension of univariate Chebyshev polynomials of the first kind to the multivariate setting, where one chases best approximants to specific monomials by polynomials of lower degree relative to the uniform…

Optimization and Control · Mathematics 2024-10-29 Mareike Dressler , Simon Foucart , Mioara Joldes , Etienne de Klerk , Jean Bernard Lasserre , Yuan Xu

This paper presents an algorithm to simulate Gaussian random vectors whose precision matrix can be expressed as a polynomial of a sparse matrix. This situation arises in particular when simulating Gaussian Markov random fields obtained by…

Methodology · Statistics 2020-04-07 Mike Pereira , Nicolas Desassis

} The main goal of this note is to provide new, mostly multidimensional densities, compactly supported and list many of its properties that enable effective calculations. The idea of obtaining such densities is firstly to build some…

Classical Analysis and ODEs · Mathematics 2018-08-08 Paweł J. Szabłowski

When implementing regular enough functions (e.g., elementary or special functions) on a computing system, we frequently use polynomial approximations. In most cases, the polynomial that best approximates (for a given distance and in a given…

Mathematical Software · Computer Science 2007-05-23 Nicolas Brisebarre , Jean-Michel Muller

Let $X$ be a compact metric space, $C(X)$ be the space of continuous real-valued functions on $X$, and $A_1$, $A_2$ be two closed subalgebras of $C(X)$ containing constant functions. We consider the problem of approximation of a function…

Functional Analysis · Mathematics 2023-11-27 Aida Asgarova , Ali Huseynli , Vugar Ismailov

In this work, we discuss the problem of approximating a multivariate function by discrete least squares projection onto a polynomial space using a specially designed deterministic point set. The independent variables of the function are…

Numerical Analysis · Mathematics 2014-01-07 Tao Zhou , Akil Narayan , Zhiqiang Xu

A theorem is proved concerning approximation of analytic functions by multivariate polynomials in the $s$-dimensional hypercube. The geometric convergence rate is determined not by the usual notion of degree of a multivariate polynomial,…

Numerical Analysis · Mathematics 2016-08-09 Lloyd N. Trefethen

The estimates of the uniform norm of the Chebyshev polynomials associated with a compact set $K$ in the complex plane are established. These estimates are exact (up to a constant factor) in the case where $K$ consists of a finite number of…

Complex Variables · Mathematics 2017-01-24 Vladimir Andrievskii

This paper describes a novel method to approximate the polynomial coefficients of regression functions, with particular interest on multi-dimensional classification. The derivation is simple, and offers a fast, robust classification…

Machine Learning · Statistics 2012-03-27 Péter Kövesárki

In this work, considering a general subclass of bi-univalent functions and using the Chebyshev polynomials, we obtain coefficient expansions for functions in this class.

Complex Variables · Mathematics 2017-02-10 Sahsene Altinkaya , Sibel Yalcin

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

In this paper, sufficient conditions for the existence of trigonometric Hermite-Jacobi appro\-ximations of a system of functions that are sums of convergent Fourier series are found. Based on these results, sufficient conditions are…

Classical Analysis and ODEs · Mathematics 2025-10-10 A. P. Starovoitov , I. V. Kruglikov

We propose a new method of calculation of generating functions of Chebyshev polynomials in several variables associated with root systems of simple Lie algebras. We obtain the generating functions of the polynomials in two variables…

Mathematical Physics · Physics 2015-11-18 E. V. Damaskinsky , P. P. Kulish , M. A. Sokolov

The Chebyshev polynomials are utilized in this study to define the subclass of the bi-univalent function. Also, Chebyshev polynomial bounds and Fekete-Szego inequalities for functions defined in the classes are established.

Complex Variables · Mathematics 2022-09-20 G. M. Birajdar , N. D. Sangle

In this survey, we use (more or less) elementary means to establish the well-known result that for any given smooth multivariate function, the respective multivariate Bernstein polynomials converge to that function in all derivatives on…

Classical Analysis and ODEs · Mathematics 2016-09-08 Adrian Fellhauer