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Our purpose in this paper is to apply the general methodology for model selection based on T-estimators developed in Birg\'{e} [Ann. Inst. H. Poincar\'{e} Probab. Statist. 42 (2006) 273--325] to the particular situation of the estimation of…

Statistics Theory · Mathematics 2009-09-29 Lucien Birgé

In this work we study a residual based a posteriori error estimation for the CutFEM method applied to an elliptic model problem. We consider the problem with non-polygonal boundary and the analysis takes into account the geometry and data…

Numerical Analysis · Mathematics 2024-09-23 Erik Burman , Cuiyu He , Mats G. Larson

In this paper we analyze a posteriori error estimates for a mixed formulation of the linear elasticity eigenvalue problem. A posteriori estimators for the nearly and perfectly compressible elasticity spectral problems are proposed. With a…

Numerical Analysis · Mathematics 2022-01-12 Felipe Lepe , Gonzalo Rivera , Jesús Vellojín

Adaptive atomistic/continuum (a/c) coupling method is an important method for the simulation of material and atomistic systems with defects to achieve the balance of accuracy and efficiency. Residual based a posteriori error estimator is…

Numerical Analysis · Mathematics 2022-11-28 Yangshuai Wang , Hao Wang

Truncated Taylor series representations of invariant manifolds are abundant in numerical computations. We present an aposteriori method to compute the convergence radii and error estimates of analytic parametrisations of non-resonant local…

Dynamical Systems · Mathematics 2011-03-09 Tomas Johnson , Warwick Tucker

We propose a method of obtaining a posteriori estimates which does not use the duality theory and which applies to variational inequalities with monotone operators, without assuming the potentiality of operators. The effectiveness of the…

Analysis of PDEs · Mathematics 2025-04-15 Vladimir Bobkov , Svetlana Pastukhova

Defeaturing, the process of simplifying computational geometries, is a critical step in industrial simulation pipelines for reducing computational cost. Rigorous a posteriori estimators exist for the global energy-norm error introduced by…

Numerical Analysis · Mathematics 2025-12-24 Philipp Weder , Annalisa Buffa

We propose a novel a posteriori error estimator for the N\'ed\'elec finite element discretization of time-harmonic Maxwell's equations. After the approximation of the electric field is computed, we propose a fully localized algorithm to…

Numerical Analysis · Mathematics 2024-02-28 T. Chaumont-Frelet

We consider a priori estimates of possibly sign-changing solutions to superlinear parabolic problems and their applications (blow-up rates, energy blow-up, continuity of blow-up time, existence of nontrivial steady states etc). Our…

Analysis of PDEs · Mathematics 2025-01-23 Pavol Quittner

We derive a fully computable aposteriori error estimator for a Galerkin finite element solution of the wave equation with explicit leapfrog time-stepping. Our discrete formulation accommodates both time evolving meshes and leapfrog based…

Numerical Analysis · Mathematics 2025-06-27 Marcus J. Grote , Omar Lakkis , Carina Santos

In certain applications involving the solution of a Bayesian inverse problem, it may not be possible or desirable to evaluate the full posterior, e.g. due to the high computational cost of doing so. This problem motivates the use of…

Statistics Theory · Mathematics 2024-02-27 Han Cheng Lie , T. J. Sullivan , Aretha Teckentrup

The paper offers a unified approach to the study of three locally adaptive estimation methods in the context of univariate time series from both theoretical and empirical points of view. A general procedure for the computation of critical…

Statistics Theory · Mathematics 2008-12-03 Mstislav Elagin

We recently proposed a general algorithm for approximating nonstandard Bayesian posterior distributions by minimization of their Kullback-Leibler divergence with respect to a more convenient approximating distribution. In this note we offer…

Computation · Statistics 2014-01-10 Tim Salimans

Conditional estimation given specific covariate values (i.e., local conditional estimation or functional estimation) is ubiquitously useful with applications in engineering, social and natural sciences. Existing data-driven non-parametric…

Machine Learning · Statistics 2020-10-13 Viet Anh Nguyen , Fan Zhang , Jose Blanchet , Erick Delage , Yinyu Ye

A widely used electrostatics model in the biomolecular modeling community, the nonlinear Poisson-Boltzmann equation, along with its finite element approximation, are analyzed in this paper. A regularized Poisson-Boltzmann equation is…

Numerical Analysis · Mathematics 2010-01-12 Long Chen , Michael Holst , Jinchao Xu

We present a posteriori error analysis in the supremum norm for the symmetric interior penalty discontinuous Galerkin method for the elliptic obstacle problem. We construct discrete barrier functions based on appropriate corrections of the…

Numerical Analysis · Mathematics 2021-08-27 Blanca Ayuso de Dios , Thirupathi Gudi , Kamana Porwal

This work concerns with the discontinuous Galerkin (DG)method for the time-dependent linear elasticity problem. We derive the a posteriori error bounds for semi-discrete and fully discrete problems, by making use of the stationary…

Numerical Analysis · Mathematics 2015-06-11 Thi Hong Cam Luong , Christian Daveau

We analyze a reliable and efficient max-norm a posteriori error estimator for a control-constrained, linear-quadratic optimal control problem. The estimator yields optimal experimental rates of convergence within an adaptive loop.

Numerical Analysis · Mathematics 2017-11-21 Alejandro Allendes , Enrique Otarola , Richard Rankin , Abner J. Salgado

The multiple-network poroelasticity (MPET) equations describe deformation and pressures in an elastic medium permeated by interacting fluid networks. In this paper, we (i) place these equations in the theoretical context of coupled…

Numerical Analysis · Mathematics 2022-11-16 Emilie Eliseussen , Marie E. Rognes , Travis B. Thompson

We develop an estimator for the high-dimensional covariance matrix of a locally stationary process with a smoothly varying trend and use this statistic to derive consistent predictors in non-stationary time series. In contrast to the…

Methodology · Statistics 2020-01-08 Holger Dette , Weichi Wu