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In this paper, Hermite interpolation by parametric spline surfaces on triangulations is considered. The splines interpolate points, the corresponding tangent planes and normal curvature forms at domain vertices and approximate tangent…

Numerical Analysis · Mathematics 2019-09-26 Gasper Jaklic , Tadej Kanduc

We present an algorithm to compute best least-squares approximations of discrete real-valued functions by first-degree splines (broken lines) with free knots. We demonstrate that the algorithm delivers after a finite number of steps a…

Numerical Analysis · Mathematics 2017-04-20 Ludwig J. Cromme , Jens Kunath , Andreas Krebs

This paper provides approximation orders for a class of nonlinear interpolation procedures for univariate data sampled over $\sigma$ quasi-uniform grids. The considered interpolation is built using both essentially nonoscillatory (ENO) and…

Numerical Analysis · Mathematics 2026-04-10 J. A. Padilla , J. C. Trillo

We describe a general approach for constructing a broad class of operators approximating high-dimensional curves based on geometric Hermite data. The geometric Hermite data consists of point samples and their associated tangent vectors of…

Numerical Analysis · Mathematics 2022-03-08 Hofit Ben-Zion Vardi , Nira Dyn , Nir Sharon

We consider the problem of numerical approximation of integrals of random fields over a unit hypercube. We use a stratified Monte Carlo quadrature and measure the approximation performance by the mean squared error. The quadrature is…

Probability · Mathematics 2011-05-05 Konrad Abramowicz , Oleg Seleznjev

This paper addresses asymptotic properties of general penalized spline estimators with an arbitrary B-spline degree and an arbitrary order difference penalty. The estimator is approximated by a solution of a linear differential equation…

Statistics Theory · Mathematics 2009-12-10 Xiao Wang , Jinglai Shen , David Ruppert

A determinantal point process is a stochastic point process that is commonly used to capture negative correlations. It has become increasingly popular in machine learning in recent years. Sampling a determinantal point process however…

Numerical Analysis · Mathematics 2020-09-02 Lexing Ying

We consider continuous-time sparse stochastic processes from which we have only a finite number of noisy/noiseless samples. Our goal is to estimate the noiseless samples (denoising) and the signal in-between (interpolation problem). By…

Machine Learning · Computer Science 2015-06-11 Arash Amini , Ulugbek S. Kamilov , Emrah Bostan , Michael Unser

In this paper we analyse the pathwise approximation of stochastic differential equations by polynomial splines with free knots. The pathwise distance between the solution and its approximation is measured globally on the unit interval in…

Probability · Mathematics 2013-09-12 Mehdi Slassi

Observations made in continuous time are often irregular and contain the missing values across different channels. One approach to handle the missing data is imputing it using splines, by fitting the piecewise polynomials to the observed…

Machine Learning · Computer Science 2022-10-20 Marin Biloš , Emanuel Ramneantu , Stephan Günnemann

In this paper we provide a priori error estimates in standard Sobolev (semi-)norms for approximation in spline spaces of maximal smoothness on arbitrary grids. The error estimates are expressed in terms of a power of the maximal grid…

Numerical Analysis · Mathematics 2019-07-09 Espen Sande , Carla Manni , Hendrik Speleers

In this paper, we develop approximation error estimates as well as corresponding inverse inequalities for B-splines of maximum smoothness, where both the function to be approximated and the approximation error are measured in standard…

Numerical Analysis · Mathematics 2017-05-16 Stefan Takacs , Thomas Takacs

In the present work, the notion of Cubic Spline Super Fractal Interpolation Function (SFIF) is introduced to simulate an object that depicts one structure embedded into another and its approximation properties are investigated. It is shown…

Dynamical Systems · Mathematics 2015-06-03 G. P. Kapoor , Srijanani Anurag Prasad

We propose a novel method to determine the dissimilarity between subjects for functional data clustering. Spline smoothing or interpolation is common to deal with data of such type. Instead of estimating the best-representing curve for each…

Methodology · Statistics 2021-03-23 ShengLi Tzeng , Christian Hennig , Yu-Fen Li , Chien-Ju Lin

Consider the problem when $X_1,X_2,..., X_n$ are distributed on a circle following an unknown distribution $F$ on $S^1$. In this article we have consider the absolute general set-up where the density can have local features such as…

Methodology · Statistics 2016-11-26 Kinjal Basu , Debapriya Sengupta

We consider the weighted least squares spline approximation of a noisy dataset. By interpreting the weights as a probability distribution, we maximize the associated entropy subject to the constraint that the mean squared error is…

Numerical Analysis · Mathematics 2024-01-19 Luigi Brugnano , Domenico Giordano , Felice Iavernaro , Giorgia Rubino

Hermite processes are self--similar processes with stationary increments which appear as limits of normalized sums of random variables with long range dependence. The Hermite process of order $1$ is fractional Brownian motion and the…

Probability · Mathematics 2014-07-22 Marianne Clausel , François Roueff , Murad Taqqu , Ciprian A. Tudor

We consider a modified quadratic variation of the Hermite process based on some well-chosen increments of this process. These special increments have the very useful property to be independent and identically distributed up to…

Probability · Mathematics 2023-04-24 Antoine Ayache , Ciprian A Tudor

The problem of extrapolation and interpolation of asymptotic series is considered. Several new variants of improving the accuracy of the self-similar approximants are suggested. The methods are illustrated by examples typical of chemical…

Mathematical Physics · Physics 2010-04-08 V. I. Yukalov , E. P. Yukalova , S. Gluzman

In this work, we study the Hermite interpolation on $n$-dimensional non-equally spaced, rectilinear grids over a field $\Bbbk $ of characteristic zero, given the values of the function at each point of the grid and the partial derivatives…