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We propose new a posteriori error estimators for non-conforming finite element discretizations of second-order elliptic PDE problems. These estimators are based on novel reformulations of the standard Prager-Synge identity, and enable to…

Numerical Analysis · Mathematics 2026-01-22 T. Chaumont-Frelet

Many spatial processes exhibit nonstationary features. We estimate a variance function from a single process observation where the errors are nonstationary and correlated. We propose a difference-based approach for a one-dimensional…

Methodology · Statistics 2016-05-24 Eunice J. Kim , Zhengyuan Zhu

A general a posteriori error analysis applies to five lowest-order finite element methods for two fourth-order semi-linear problems with trilinear non-linearity and a general source. A quasi-optimal smoother extends the source term to the…

Numerical Analysis · Mathematics 2023-09-18 Carsten Carstensen , Benedikt Gräßle , Neela Nataraj

We consider in this paper, a new a posteriori residual type error estimator of a conforming mixed finite element method for the coupling of fluid flow with porous media flow on isotropic meshes. Flows are governed by the Navier-Stokes and…

Numerical Analysis · Mathematics 2017-03-07 Koffi Wilfrid Houedanou , Jamal Adetola , Bernardin Ahounou

We propose a general algorithm for approximating nonstandard Bayesian posterior distributions. The algorithm minimizes the Kullback-Leibler divergence of an approximating distribution to the intractable posterior distribution. Our method…

Computation · Statistics 2014-07-29 Tim Salimans , David A. Knowles

This article presents a general and novel approach to the automation of goal-oriented error control in the solution of nonlinear stationary finite element variational problems. The approach is based on automated linearization to obtain the…

Numerical Analysis · Mathematics 2012-05-01 Marie E. Rognes , Anders Logg

We consider a conforming finite element approximation of the Reissner-Mindlin system. We propose a new robust a posteriori error estimator based on H(div) conforming finite elements and equilibrated fluxes. It is shown that this estimator…

Numerical Analysis · Mathematics 2010-11-04 Emmanuel Creusé , Serge Nicaise , Emmanuel Verhille

A general framework for goal-oriented a posteriori error estimation for finite volume methods is presented. The framework does not rely on recasting finite volume methods as special cases of finite element methods, but instead directly…

Numerical Analysis · Mathematics 2011-08-24 Qingshan Chen , Max Gunzburger

The Richards equation is commonly used to model the flow of water and air through soil, and it serves as a gateway equation for multiphase flows through porous media. It is a nonlinear advection-reaction-diffusion equation that exhibits…

Numerical Analysis · Mathematics 2021-08-31 K. Mitra , M. Vohralík

We present functional-type a posteriori error estimates in isogeometric analysis. These estimates, derived on functional grounds, provide guaranteed and sharp upper bounds of the exact error in the energy norm. {Moreover, since these…

Numerical Analysis · Mathematics 2014-09-23 Stefan K. Kleiss , Satyendra K. Tomar

A posteriori error analysis is a technique to quantify the error in particular simulations of a numerical approximation method. In this article, we use such an approach to analyze how various error components propagate in certain moving…

Numerical Analysis · Mathematics 2019-09-04 Jay A. Stotsky , David M. Bortz

We consider systems of ordinary differential equations with multiple scales in time. In general, we are interested in the long time horizon of a slow variable that is coupled to solution components that act on a fast scale. Although the…

Numerical Analysis · Mathematics 2021-04-28 Leopold Lautsch , Thomas Richter

In this work we develop an a posteriori error analysis of a conforming mixed finite element method for solving the coupled problem arising in the interaction between a free fluid and a fluid in a poroelastic medium on isotropic meshes in…

Numerical Analysis · Mathematics 2020-04-23 Koffi Wilfrid Houédanou

We present a method of parameter estimation for large class of nonlinear systems, namely those in which the state consists of output derivatives and the flow is linear in the parameter. The method, which solves for the unknown parameter by…

Systems and Control · Electrical Eng. & Systems 2024-07-16 Simon Kuang , Xinfan Lin

Local polynomial regression of order at least one often performs poorly in regions of sparse data. Local constant regression is exceptional in this regard, though it is the least accurate method in general, especially at the boundaries of…

Methodology · Statistics 2024-06-18 Chunlei Ge , W. John Braun

This paper aims to build an estimate of an unknown density of the data with measurement error as a linear combination of functions from a dictionary. Inspired by the penalization approach, we propose the weighted Elastic-net penalized…

Statistics Theory · Mathematics 2020-07-07 Xiaowei Yang , Huiming Zhang , Haoyu Wei , Shouzheng Zhang

Residual-based a~posteriori error estimators are derived for the modified Morley FEM, proposed by Wang, Xu, Hu [J. Comput. Math, 24(2), 2006], for the singularly perturbed biharmonic equation and the nonlinear von K\'arm\'an equations. The…

Numerical Analysis · Mathematics 2026-02-17 A. K. Dond , D. Gallistl , S. Nayak , M. Schedensack

Estimators derived from score functions that are not the likelihood are in wide use in practical and modern applications. Their regularization is often carried by pseudo-posterior estimation, equivalently by adding penalty to the score…

Methodology · Statistics 2020-11-17 Erez Buchweitz , Shlomo Ahal , Oded Papish , Guy Adini

This paper is concerned with the analysis and numerical analysis for the optimal control of first-order magneto-static equations. Necessary and sufficient optimality conditions are established through a rigorous Hilbert space approach.…

Numerical Analysis · Mathematics 2016-07-19 Dirk Pauly , Irwin Yousept

The propensity score is widely used for causal inference in observational studies, but common parametric estimators can produce biased and inefficient effect estimates when model assumptions are violated. Nonparametric approaches reduce…

Methodology · Statistics 2026-04-09 Maosen Peng , Yan Li , Chong Wu , Liang Li