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The well-known Prager-Synge identity is valid in $H^1(\Omega)$ and serves as a foundation for developing equilibrated a posteriori error estimators for continuous elements. In this paper, we introduce a new inequality, that may be regarded…

Numerical Analysis · Mathematics 2020-01-27 Cuiyu He , Zhiqiang Cai , Shun Zhang

Finite mixture models are widely used in econometric analyses to capture unobserved heterogeneity. This paper shows that maximum likelihood estimation of finite mixtures of parametric densities can suffer from substantial finite-sample bias…

Methodology · Statistics 2026-02-04 Raphaël Langevin

The statistical finite element method (StatFEM) is an emerging probabilistic method that allows observations of a physical system to be synthesised with the numerical solution of a PDE intended to describe it in a coherent statistical…

Numerical Analysis · Mathematics 2022-02-21 Yanni Papandreou , Jon Cockayne , Mark Girolami , Andrew B. Duncan

Every element $\theta=(\theta_1,\ldots,\theta_n)$ of the probability $n$-simplex induces a probability distribution $P_\theta$ of a random variable $X$ that can assume only a finite number of real values $x_1 < \cdots < x_n$ by defining…

Probability · Mathematics 2020-09-08 S. Fried

In this paper, we are concerned with the convergence rate of a FEM based numerical scheme approximating extremal functions of the Sobolev inequality. We prove that when the domain is polygonal and convex in $\R^2$, the convergence of a…

Numerical Analysis · Mathematics 2018-09-27 Woocheol Choi , Younghun Hong , Jinmyoung Seok

Every student in statistics or data science learns early on that when the sample size largely exceeds the number of variables, fitting a logistic model produces estimates that are approximately unbiased. Every student also learns that there…

Statistics Theory · Mathematics 2022-06-08 Pragya Sur , Emmanuel J. Candes

We study the approximability of instances of the minimum entropy set cover problem, parameterized by the average frequency of a random element in the covering sets. We analyze an algorithm combining a greedy approach with another one biased…

Data Structures and Algorithms · Computer Science 2012-08-01 Cosmin Bonchis , Gabriel Istrate

For many applications, an ensemble of base classifiers is an effective solution. The tuning of its parameters(number of classes, amount of data on which each classifier is to be trained on, etc.) requires G, the generalization error of a…

Finite differences, finite elements, and their generalizations are widely used for solving partial differential equations, and their high-order variants have respective advantages and disadvantages. Traditionally, these methods are treated…

Numerical Analysis · Mathematics 2020-01-22 Rebecca Conley , Xiangmin Jiao , Tristan J. Delaney

Let (X_n,Y_n) be i.i.d. random vectors. Let W(x) be the partial sum of Y_n just before that of X_n exceeds x>0. Motivated by stochastic models for neural activity, uniform convergence of the form $\sup_{c\in I}|a(c,x)\operatorname…

Probability · Mathematics 2009-09-29 Zhiyi Chi

Given a stream of Bernoulli random variables, consider the problem of estimating the mean of the random variable within a specified relative error with a specified probability of failure. Until now, the Gamma Bernoulli Approximation Scheme…

Machine Learning · Computer Science 2022-10-25 Mark Huber

We study the weak finite element method solving convection-diffusion equations. A weak finite element scheme is presented based on a spacial variational form. We established a weak embedding inequality that is very useful in the weak finite…

Numerical Analysis · Mathematics 2015-06-10 Tie Zhang , Yanli Chen

We present a novel probabilistic finite element method (FEM) for the solution and uncertainty quantification of elliptic partial differential equations based on random meshes, which we call random mesh FEM (RM-FEM). Our methodology allows…

Numerical Analysis · Mathematics 2021-06-17 Assyr Abdulle , Giacomo Garegnani

We study the problem of generalized uniformity testing \cite{BC17} of a discrete probability distribution: Given samples from a probability distribution $p$ over an {\em unknown} discrete domain $\mathbf{\Omega}$, we want to distinguish,…

Data Structures and Algorithms · Computer Science 2017-09-08 Ilias Diakonikolas , Daniel M. Kane , Alistair Stewart

In this paper, we study a generalized finite element method for solving second-order elliptic partial differential equations with rough coefficients. The method uses local approximation spaces computed by solving eigenvalue problems on…

Numerical Analysis · Mathematics 2025-07-17 Christian Alber , Peter Bastian , Moritz Hauck , Robert Scheichl

We propose skewed stable random projections for approximating the pth frequency moments of dynamic data streams (0<p<=2), which has been frequently studied in theoretical computer science and database communities. Our method significantly…

Data Structures and Algorithms · Computer Science 2008-02-07 Ping Li

We prove a rate of convergence for finite element approximations of stationary, second-order mean field games with nondifferentiable Hamiltonians posed in general bounded polytopal Lipschitz domains with strongly monotone running costs. In…

Numerical Analysis · Mathematics 2026-03-20 Yohance A. P. Osborne , Iain Smears

The object of this paper is a one-dimensional generalized porous media equation (PDE) with possibly discontinuous coefficient $\beta$, which is well-posed as an evolution problem in $L^1(\mathbb{R})$. In some recent papers of Blanchard et…

Probability · Mathematics 2010-11-17 Nadia Belaribi , François Cuvelier , Francesco Russo

We study the question of closeness testing for two discrete distributions. More precisely, given samples from two distributions $p$ and $q$ over an $n$-element set, we wish to distinguish whether $p=q$ versus $p$ is at least $\eps$-far from…

Data Structures and Algorithms · Computer Science 2013-08-20 Siu-On Chan , Ilias Diakonikolas , Gregory Valiant , Paul Valiant

This article discusses the problem of estimation of parameters in finite mixtures when the mixture components are assumed to be symmetric and to come from the same location family. We refer to these mixtures as semi-parametric because no…

Statistics Theory · Mathematics 2007-08-07 David R. Hunter , Shaoli Wang , Thomas P. Hettmansperger