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Weighting procedures are used in observational causal inference to adjust for covariate imbalance within the sample. Common practice for inference is to estimate robust standard errors from a weighted regression of outcome on treatment.…

Methodology · Statistics 2025-07-29 Erin Hartman , Chad Hazlett , Arisa Sadeghpour

Electronic health records and other sources of observational data are increasingly used for drawing causal inferences. The estimation of a causal effect using these data not meant for research purposes is subject to confounding and…

Methodology · Statistics 2023-04-19 Janie Coulombe , Shu Yang

We present a local weighted estimate for the Riesz potential in $\mathbb{R}^n$, which improves the main theorem of Alberico, Cianchi, and Sbordone [C. R. Math. Acad. Sci. Paris \textbf{347} (2009)] in several ways. As a consequence, we…

Classical Analysis and ODEs · Mathematics 2025-12-04 Alejandro Claros

Increased availability of data and accessibility of computational tools in recent years have created unprecedented opportunities for scientific research driven by statistical analysis. Inherent limitations of statistics impose constrains on…

Genomics · Quantitative Biology 2016-09-13 Olga A. Vsevolozhskaya , Gabriel Ruiz , Dmitri V. Zaykin

We propose a versatile and computationally efficient estimating equation method for a class of hierarchical multiplicative generalized linear mixed models with additive dispersion components, based on explicit modelling of the covariance…

Methodology · Statistics 2010-08-18 René Holst , Bent Jørgensen

Belief propagation (BP) is a powerful tool to solve distributed inference problems, though it is limited by short cycles in the corresponding factor graph. Such cycles may lead to incorrect solutions or oscillatory behavior. Only for…

Systems and Control · Computer Science 2018-02-08 Christopher Lindberg , Julien M. Hendrickx , Henk Wymeersch

We develop a new method for frequentist multiple testing with Bayesian prior information. Our procedure finds a new set of optimal p-value weights called the Bayes weights. Prior information is relevant to many multiple testing problems.…

Methodology · Statistics 2017-10-03 Edgar Dobriban , Kristen Fortney , Stuart K. Kim , Art B. Owen

In this paper we study the asymptotic behaviour of weighted random sums when the sum process converges stably in law to a Brownian motion and the weight process has continuous trajectories, more regular than that of a Brownian motion. We…

Probability · Mathematics 2014-02-07 José Manuel Corcuera , David Nualart , Mark Podolskij

The main goal of this paper is twofold. First, it characterizes the existence of positive periodic solutions for a general class of weighted periodic-parabolic logistic problems of degenerate type (see (1.1)). This result provides us with…

Analysis of PDEs · Mathematics 2021-10-28 D. Aleja , I. Antón , J. López-Gómez

The method of self-consistent expansions is a powerful tool for handling strong coupling problems that might otherwise be beyond the reach of perturbation theory, providing surprisingly accurate approximations even at low order. First…

Statistical Mechanics · Physics 2025-01-15 Minhui Zhu , Nigel Goldenfeld

Uniformly regular equilibrium problems are natural generalizations of abstract equilibrium prob lems and they are defined over the uniformly prox-regular nonconvex sets. Some new efficient implicit methods for solving uniformly regular…

Optimization and Control · Mathematics 2025-02-11 Oday Hazaimah

It is well known that general variational inequalities provide us with a unified, natural, novel and simple framework to study a wide class of unrelated problems, which arise in pure and applied sciences. In this paper, we present a number…

Optimization and Control · Mathematics 2020-09-24 M. A. Noor , K. I. Noor , M. Th. Rassias

In this paper, we obtain the exact controllability for a refined stochastic wave equation with three controls by establishing a novel Carleman estimate for a backward hyperbolic-like operator. Compared with the known result, the novelty of…

Optimization and Control · Mathematics 2023-09-21 Zhonghua Liao , Qi Lü

I present a new, simple method to dynamically control the growth of the discretized constraints during a free evolution of Einstein's equations. During an evolution, any given family of formulations is adjusted off the constraints surface…

General Relativity and Quantum Cosmology · Physics 2007-05-23 Manuel Tiglio

Instrumental variable analysis is a powerful tool for estimating causal effects when randomization or full control of confounders is not possible. The application of standard methods such as 2SLS, GMM, and more recent variants are…

Machine Learning · Statistics 2020-06-08 Andrew Bennett , Nathan Kallus , Tobias Schnabel

The computational cost of solving an inverse problem governed by PDEs, using multiple experiments, increases linearly with the number of experiments. A recently proposed method to decrease this cost uses only a small number of random linear…

Optimization and Control · Mathematics 2017-08-02 Benjamin Crestel , Alen Alexanderian , Georg Stadler , Omar Ghattas

We obtain estimates for Vinogradov's integral which for the first time approach those conjectured to be the best possible. Several applications of these new bounds are provided. In particular, the conjectured asymptotic formula in Waring's…

Number Theory · Mathematics 2012-08-13 Trevor D. Wooley

The extended definition of the polynomial B-splines may give a chance to improve the results obtained by the classical cubic polynomial B-splines. Determination of the optimum value of the extension parameter can be achieved by scanning…

Numerical Analysis · Mathematics 2017-02-10 Ozlem Ersoy Hepson , Alper Korkmaz , Idris Dag

In this paper we provide a probabilistic representation of Lagrange's identity which we use to obtain Papathanasiou-type variance expansions of arbitrary order. Our expansions lead to generalized sequences of weights which depend on an…

Probability · Mathematics 2019-06-21 Marie Ernst , Gesine Reinert , Yvik Swan

One method for the numerical treatment of future null-infinity is to decouple coordinates from the tensor basis and choose each in a careful manner. This dual-frame approach is hampered by logarithmically divergent terms that appear in a…

General Relativity and Quantum Cosmology · Physics 2020-01-29 Edgar Gasperin , Shalabh Gautam , David Hilditch , Alex Vañó-Viñuales
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