English
Related papers

Related papers: Algebraic polynomials and moments of stochastic in…

200 papers

We discuss the probabilistic properties of the variation based third and fourth moments of financial returns as estimators of the actual moments of the return distributions. The moment variations are defined under non-parametric assumptions…

Statistical Finance · Quantitative Finance 2019-08-15 Kyungsub Lee

A general device is proposed, which provides for extension of exponential inequalities for sums of independent real-valued random variables to those for martingales in the 2-smooth Banach spaces. This is used to obtain optimum bounds of the…

Probability · Mathematics 2012-12-11 Iosif Pinelis

Acoustic emission or scattering problems naturally involve uncertainties about the sound sources or boundary conditions. This article initiates the study of time domain boundary elements for such stochastic boundary problems for the…

Numerical Analysis · Mathematics 2024-07-23 Heiko Gimperlein , Fabian Meyer , Ceyhun Özdemir

In this paper non-asymptotic exponential estimates are derived for the tail distribution of polynomial martingale differences in terms unconditional tails distributions of summands. Applications are considered in the theory of polynomials…

Probability · Mathematics 2007-05-23 Eugene Ostrovsky

A new method of algebraic nature is proposed for the study of the asymptotic properties of special polynomials. The technique we foresee is based on the use of umbral operators, allowing a unified treatment of a large body of polynomial…

Classical Analysis and ODEs · Mathematics 2020-02-18 G. Dattoli , S. Licciardi , R. M. Pidatella , E. Sabia

We derive sufficient conditions for the differentiability of all orders for the flow of stochastic differential equations with jumps, and prove related $L^p$-integrability results for all orders. Our results extend similar results obtained…

Probability · Mathematics 2021-01-12 Jean-Christophe Breton , Nicolas Privault

Several recent works have explored stochastic gradient methods for variational inference that exploit the geometry of the variational-parameter space. However, the theoretical properties of these methods are not well-understood and these…

Machine Learning · Statistics 2016-08-15 Mohammad Emtiyaz Khan , Reza Babanezhad , Wu Lin , Mark Schmidt , Masashi Sugiyama

The mixed moments for the Askey-Wilson polynomials are found using a bootstrapping method and connection coefficients. A similar bootstrapping idea on generating functions gives a new Askey-Wilson generating function. An important special…

Classical Analysis and ODEs · Mathematics 2014-03-04 Jang Soo Kim , Dennis Stanton

The main purpose of this paper is to prove some density results of polynomials in Fock spaces of slice regular functions. The spaces can be of two different kinds since they are equipped with different inner products and contain different…

Complex Variables · Mathematics 2018-12-10 Kamal Diki , Sorin G. Gal , Irene Sabadini

Compartmentalised biochemical reactions are a ubiquitous building block of biological systems. The interplay between chemical and compartmental dynamics can drive rich and complex dynamical behaviors that are difficult to analyse…

Molecular Networks · Quantitative Biology 2023-06-16 Tommaso Bianucci , Christoph Zechner

We describe a method for calculating the roots of special functions satisfying second order linear ordinary differential equations. It exploits the recent observation that the solutions of a large class of such equations can be represented…

Numerical Analysis · Mathematics 2016-08-05 James Bremer

By combining the telescoping method with an algebraic relation, four classes of binomial moments are examined. Several explicit summation formulae are established.

Combinatorics · Mathematics 2026-03-30 Marta Na Chen , Wenchang Chu

We derive a discrete version of the stochastic Gronwall Lemma found in [Scheutzow, IDAQP, 2013]. The proof is based on a corresponding deterministic version of the discrete Gronwall Lemma and an inequality bounding the supremum in terms of…

Probability · Mathematics 2017-01-16 Raphael Kruse , Michael Scheutzow

We prove that several forms of the Bernstein polynomials with integer coefficients possess the property of simultaneous approximation, that is, they approximate not only the function but also its derivatives. We establish direct estimates…

Classical Analysis and ODEs · Mathematics 2019-04-23 Borislav R. Draganov

In this paper, we study the existence of random periodic solutions for semilinear stochastic differential equations. We identify these as the solutions of coupled forward-backward infinite horizon stochastic integral equations in general…

Probability · Mathematics 2015-02-11 Chunrong Feng , Huaizhong Zhao , Bo Zhou

The quality of numerical computations can be measured through their forward error, for which finding good error bounds is challenging in general. For several algorithms and using stochastic rounding (SR), probabilistic analysis has been…

Computation · Statistics 2025-08-29 Pablo de Oliveira Castro , El-Mehdi El Arar , Eric Petit , Devan Sohier

Starting with some fundamental concepts, in this article we present the essential aspects of spectral methods and their applications to the numerical solution of Partial Differential Equations (PDEs). We start by using Lagrange and…

Numerical Analysis · Mathematics 2014-03-25 Samir Kumar Bhowmik , Sharanjeet Dhawan

We propose an approach to determine the continual progression of algorithmic efficiency, as an alternative to standard calculations of time complexity, likely, but not exclusively, when dealing with data structures with unknown maximum…

Computational Complexity · Computer Science 2020-12-04 Ananth Goyal

In this work we design a general method for proving moment inequalities for polynomials of independent random variables. Our method works for a wide range of random variables including Gaussian, Boolean, exponential, Poisson and many…

Probability · Mathematics 2012-06-11 Warren Schudy , Maxim Sviridenko

Stochastic gradient methods are among the most widely used algorithms for large-scale optimization and machine learning. A key technique for improving the statistical efficiency and stability of these methods is the use of averaging schemes…

Optimization and Control · Mathematics 2026-03-11 K. Lakshmanan