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We consider nonparametric regression with functional covariates, that is, they are elements of an infinite-dimensional Hilbert space. A locally polynomial estimator is constructed, where an orthonormal basis and various tuning parameters…

Statistics Theory · Mathematics 2025-04-09 Moritz Jirak , Alois Kneip , Alexander Meister , Mario Pahl

Extension problems for polynomial valuations on different cones of convex functions are investigated. It is shown that for the classes of functions under consideration, the extension problem reduces to a simple geometric obstruction on the…

Functional Analysis · Mathematics 2024-08-14 Jonas Knoerr , Jacopo Ulivelli

We show how one can obtain an asymptotic expression for some special functions satisfying a second order differential equation with a very explicit error term starting from appropriate upper bounds. We will work out the details for the…

Classical Analysis and ODEs · Mathematics 2011-07-15 Ilia Krasikov

The paper overviews and investigates several nonparametric methods of estimating covariograms. It provides a unified approach and notation to compare the main approaches used in applied research. The primary focus is on methods that utilise…

Methodology · Statistics 2024-08-06 Adam Bilchouris , Andriy Olenko

The inverse of a large matrix can often be accurately approximated by a polynomial of degree significantly lower than the order of the matrix. The iteration polynomial generated by a run of the GMRES algorithm is a good candidate, and its…

Numerical Analysis · Mathematics 2025-02-26 Mark Embree , Joel A. Henningsen , Jordan Jackson , Ronald B. Morgan

In the paper, the authors first inductively establish explicit formulas for derivatives of the arc sine function, then derive from these explicit formulas explicit expressions for a family of Bell polynomials related to the square function,…

Classical Analysis and ODEs · Mathematics 2015-05-12 Feng Qi , Miao-Miao Zheng

The error function of real argument can be uniformly approximated to a given accuracy by a single closed-form expression for the whole variable range either in terms of addition, multiplication, division, and square root operations only, or…

Chemical Physics · Physics 2025-10-06 Dimitri N. Laikov

Polynomial regression is widely used and can help to express nonlinear patterns. However, considering very high polynomial orders may lead to overfitting and poor extrapolation ability for unseen data. The paper presents a method for…

Machine Learning · Computer Science 2023-08-01 Andrei Ivanov , Stefan Maria Ailuro

In the multidimensional setting, we consider the errors-in-variables model. We aim at estimating the unknown nonparametric multivariate regression function with errors in the covariates. We devise an adaptive estimator based on projection…

Statistics Theory · Mathematics 2016-01-13 Michaël Chichignoud , Van Ha Hoang , Thanh Mai Pham Ngoc , Vincent Rivoirard

This paper shows how to build a formal analytical solution for a differential equation of arbitrary order and with variable coefficients. It proofs that the most known approximated solutions for such a problem can be derived from the…

Classical Analysis and ODEs · Mathematics 2015-05-26 Mauro Bologna

We derive an extended empirical likelihood for parameters defined by estimating equations which generalizes the original empirical likelihood for such parameters to the full parameter space. Under mild conditions, the extended empirical…

Statistics Theory · Mathematics 2013-06-07 Min Tsao , Fan Wu

Global variational approximation methods in graphical models allow efficient approximate inference of complex posterior distributions by using a simpler model. The choice of the approximating model determines a tradeoff between the…

Artificial Intelligence · Computer Science 2013-01-14 Tal El-Hay , Nir Friedman

First-order fully implicit as well as implicit--explicit schemes for coupled elliptic-parabolic systems are discussed in [Ern and Meunier, ESAIM: M2AN, 2009] and [Altmann et al., Math.\ Comp., 2021], respectively. The extension of the…

Numerical Analysis · Mathematics 2026-01-06 Georgios Akrivis , Minghua Chen , Fan Yu

We consider in this paper an area functional defined on submanifolds of fixed degree immersed into a graded manifold equipped with a Riemannian metric. Since the expression of this area depends on the degree, not all variations are…

Differential Geometry · Mathematics 2021-12-21 Giovanna Citti , Gianmarco Giovannardi , Manuel Ritoré

With the use of the $(f,g)$-matrix inversion under specializations that $f=1-xy,g=y-x$, we establish an $(1-xy,y-x)$-expansion formula. When specialized to basic hypergeometric series, this $(1-xy,y-x)$-expansion formula leads us to some…

Combinatorics · Mathematics 2021-08-27 Jin Wang , Xinrong Ma

We propose a novel variational Bayes approach to estimate high-dimensional vector autoregression (VAR) models with hierarchical shrinkage priors. Our approach does not rely on a conventional structural VAR representation of the parameter…

Econometrics · Economics 2023-07-03 Mauro Bernardi , Daniele Bianchi , Nicolas Bianco

In this note, by using the Hasse-Teichm\"uller derivatives, we obtain two explicit expressions for the related numbers of higher order Appell polynomials. One of them presents a determinant expression for the related numbers of higher order…

Number Theory · Mathematics 2018-06-18 Su Hu , Takao Komatsu

New explicit expressions are derived for the one-loop two-point Feynman integral with arbitrary external momentum and masses $m_1^2$ and $m_2^2$ in D dimensions. The results are given in terms of Appell functions, manifestly symmetric with…

High Energy Physics - Theory · Physics 2008-11-26 M. A. Shpot

In this work we consider the Taylor expansion of the exponential map of a submanifold immersed in R^n up to order three, in order to introduce the concepts of lateral and frontal deviation. We compute the directions of extreme lateral and…

Differential Geometry · Mathematics 2012-10-23 M. G. Monera , A. Montesinos-Amilibia , E. Sanabria-Codesal

Variational methods are employed in situations where exact Bayesian inference becomes intractable due to the difficulty in performing certain integrals. Typically, variational methods postulate a tractable posterior and formulate a lower…

Machine Learning · Statistics 2019-06-12 Nikolaos Gianniotis , Christoph Schnörr , Christian Molkenthin , Sanjay Singh Bora
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