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The paper considers a class of parametric elliptic partial differential equations (PDEs), where the coefficients and the right-hand side function depend on infinitely many (uncertain) parameters. We introduce a two-level a posteriori…

Numerical Analysis · Mathematics 2021-03-18 Alex Bespalov , Dirk Praetorius , Michele Ruggeri

In two and three dimensional Lipschitz, but not necessarily convex, polytopal domains, we propose and analyze a posteriori error estimators for an optimal control problem involving the stationary Navier--Stokes equations; control…

Numerical Analysis · Mathematics 2021-01-13 Alejandro Allendes , Francisco Fuica , Enrique Otarola , Daniel Quero

We present an a posteriori error analysis for the mixed virtual element method (mixed VEM) applied to second order elliptic equations in divergence form with mixed boundary conditions. The resulting error estimator is of residual-type. It…

Numerical Analysis · Mathematics 2019-04-24 Andrea Cangiani , Mauricio Munar

Numerical approximation of the long time behavior of a stochastic differential equation (SDE) is considered. Error estimates for time-averaging estimators are obtained and then used to show that the stationary behavior of the numerical…

Probability · Mathematics 2013-11-26 Jonathan C. Mattingly , Andrew M. Stuart , M. V. Tretyakov

Many models in natural language processing define probabilistic distributions over linguistic structures. We argue that (1) the quality of a model' s posterior distribution can and should be directly evaluated, as to whether probabilities…

Computation and Language · Computer Science 2015-09-03 Khanh Nguyen , Brendan O'Connor

In this work, we derive two-sided a posteriori error estimates for the dual-weighted residual (DWR) method. We consider both single and multiple goal functionals. Using a saturation assumption, we derive lower bounds yielding the efficiency…

Numerical Analysis · Mathematics 2018-11-20 Bernhard Endtmayer , Ulrich Langer , Thomas Wick

In this paper, we propose a covariate-adjusted nonlinear regression model. In this model, both the response and predictors can only be observed after being distorted by some multiplicative factors. Because of nonlinearity, existing methods…

Statistics Theory · Mathematics 2009-08-14 Xia Cui , Wensheng Guo , Lu Lin , Lixing Zhu

Density Ratio Estimation has attracted attention from the machine learning community due to its ability to compare the underlying distributions of two datasets. However, in some applications, we want to compare distributions of random…

Machine Learning · Statistics 2020-06-26 Song Liu , Yulong Zhang , Mingxuan Yi , Mladen Kolar

We consider the problem of estimating the unconditional distribution of a post-model-selection estimator. The notion of a post-model-selection estimator here refers to the combined procedure resulting from first selecting a model (e.g., by…

Statistics Theory · Mathematics 2007-11-08 Hannes Leeb , Benedikt M. Poetscher

A novel approach to the problem of partial state estimation of nonlinear systems is proposed. The main idea is to translate the state estimation problem into one of estimation of constant, unknown parameters related to the systems initial…

Systems and Control · Computer Science 2016-04-08 Ortega Romeo , Bobtsov Alexey , Pyrkin Anton , Aranovskiy Stanislav

We consider a 1D periodic atomistic model, for which we formulate and analyze an adaptive variant of a quasicontinuum method. We establish a posteriori error estimates for the energy norm and for the energy, based on a posteriori residual…

Numerical Analysis · Mathematics 2017-02-15 Christoph Ortner , Hao Wang

Economists are often interested in estimating averages with respect to distributions of unobservables, such as moments of individual fixed-effects, or average partial effects in discrete choice models. For such quantities, we propose and…

Econometrics · Economics 2021-09-07 Stéphane Bonhomme , Martin Weidner

We consider a class of nonlinear elliptic problems associated with models in biophysics, which are described by the Poisson-Boltzmann equation (PBE). We prove mathematical correctness of the problem, study a suitable class of…

Numerical Analysis · Mathematics 2020-12-15 Johannes Kraus , Svetoslav Nakov , Sergey Repin

We establish a priori Lipschitz estimates for equations with mixed local and nonlocal diffusion, coercive gradient terms and unbounded right-hand side in Lebesgue spaces through an integral refinement of the Bernstein method. This relies on…

Analysis of PDEs · Mathematics 2022-08-01 Alessandro Goffi

Given a sample of a Poisson point process with intensity $\lambda_f(x,y) = n \mathbf{1}(f(x) \leq y),$ we study recovery of the boundary function $f$ from a nonparametric Bayes perspective. Because of the irregularity of this model, the…

Statistics Theory · Mathematics 2020-06-15 Markus Reiss , Johannes Schmidt-Hieber

In this work, we consider a multivariate regression model with one-sided errors. We assume for the regression function to lie in a general H\"{o}lder class and estimate it via a nonparametric local polynomial approach that consists of…

Statistics Theory · Mathematics 2021-02-11 Leonie Selk , Charles Tillier , Orlando Marigliano

The paper is concerned with parabolic time-periodic boundary value problems which are of theoretical interest and arise in different practical applications. The multiharmonic finite element method is well adapted to this class of parabolic…

Numerical Analysis · Mathematics 2014-11-12 Ulrich Langer , Sergey Repin , Monika Wolfmayr

We develop and analyse residual-based a posteriori error estimates for the virtual element discretisation of a nonlinear stress-assisted diffusion problem in two and three dimensions. The model problem involves a two-way coupling between…

Numerical Analysis · Mathematics 2026-02-26 Franco Dassi , Rekha Khot , Andres E. Rubiano , Ricardo Ruiz-Baier

In this paper, we give a new type of a posteriori error estimators suitable for moving finite element methods under anisotropic meshes for general second-order elliptic problems. The computation of estimators is simple once corresponding…

Numerical Analysis · Mathematics 2015-03-17 Xiaobo Yin , Hehu Xie

This paper develops a class of Bayesian non- and semiparametric methods for estimating regression curves and surfaces. The main idea is to model the regression as locally linear, and then place suitable local priors on the local parameters.…

Methodology · Statistics 2026-02-26 Nils Lid Hjort
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