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We develop a new, mathematically precise framework for treating the effects of nonlinear phenomena occurring on small scales in general relativity. Our approach is an adaptation of Burnett's formulation of the "shortwave approximation",…

General Relativity and Quantum Cosmology · Physics 2011-04-14 Stephen R. Green , Robert M. Wald

This paper introduces a novel approach to the axiomatic theory of quadratic forms. We work internally in a category of certain partially ordered sets, subject to additional conditions which amount to a strong form of local presentability.…

Rings and Algebras · Mathematics 2018-03-30 Pawel Gladki , Krzysztof Worytkiewicz

The method of quasi-optimal weights provides a comprehensive, asymptotically optimal, transparent and flexible alternative to the least squares method. The optimality holds for a general non-linear, non-gaussian case.

Data Analysis, Statistics and Probability · Physics 2009-12-16 Fyodor V. Tkachov

The phenomenology of unstable particles, including searches and exclusion limits at the LHC, depends significantly on its lineshape. When the width of the resonance is large with respect to its mass, off-shell effects become relevant and…

High Energy Physics - Phenomenology · Physics 2013-03-27 Diogo Buarque Franzosi , Fabio Maltoni , Cen Zhang

We study a popular algorithm for fitting polynomial curves to scattered data based on the least squares with gradient weights. We show that sometimes this algorithm admits a substantial reduction of complexity, and, furthermore, find…

Computational Complexity · Computer Science 2010-08-12 N. Chernov , C. Lesort , N. Simanyi

We propose a discontinuous least squares finite element method for solving the Helmholtz equation. The method is based on the L2 norm least squares functional with the weak imposition of the continuity across the interior faces as well as…

Numerical Analysis · Mathematics 2021-05-06 Ruo Li , Qicheng Liu , Fanyi Yang

It has previously been shown that ordinary least squares can be used to estimate the coefficients of the single-index model under only mild conditions. However, the estimator is non-robust leading to poor estimates for some models. In this…

Methodology · Statistics 2022-09-13 Marina Masioti , Joshua Davies , Amanda Shaker , Luke A. Prendergast

In this paper we propose a variant of the linear least squares model allowing practitioners to partition the input features into groups of variables that they require to contribute similarly to the final result. The output allows…

Machine Learning · Computer Science 2024-07-17 Roberto Esposito , Mattia Cerrato , Marco Locatelli

Weighting methods are widely used to adjust for covariates in observational studies, sample surveys, and regression settings. In this paper, we study a class of recently proposed weighting methods which find the weights of minimum…

Methodology · Statistics 2019-10-29 Yixin Wang , José R. Zubizarreta

We prove a connection between Schmidt-rank and weight of quadratic forms. This provides a new tool for the classification of graph states based on entanglement. Our main tool arises from a reformulation of previously known results…

Quantum Physics · Physics 2009-11-10 Alessandro Cosentino , Simone Severini

Heteroscedasticity is common in real world applications and is often handled by incorporating case weights into a modeling procedure. Intuitively, models fitted with different weight schemes would have a different level of complexity…

Statistics Theory · Mathematics 2022-04-15 Bo Luan , Yoonkyung Lee , Yunzhang Zhu

Concerning bivariate least squares linear regression, the classical approach pursued for functional models in earlier attempts is reviewed using a new formalism in terms of deviation (matrix) traces. Within the framework of classical error…

Instrumentation and Methods for Astrophysics · Physics 2011-03-08 R. Caimmi

In this short article, some properties of matrices of moving least-squares approximation have been proven.The used technique is based on singular-value decomposition and inequalities for singular-values. Some inequalities for the norm of…

Numerical Analysis · Mathematics 2015-10-28 Svetoslav Nenov , Tsvetelin Tsvetkov

Let $f(\mathbf x)$ be a non-singular quadratic form with sufficiently many mixed terms and $t$ an integer. For a sequence of weights $\mathcal A$ we study the number of weighted solutions to $f(\mathbf x) = t$. In particular, we give…

Number Theory · Mathematics 2025-05-26 Mieke Wessel , Svenja zur Verth

We propose a general approach to construct weighted likelihood estimating equations with the aim of obtain robust estimates. The weight, attached to each score contribution, is evaluated by comparing the statistical data depth at the model…

Methodology · Statistics 2018-02-16 Claudio Agostinelli

This paper introduces a novel adaptive framework for processing dynamic flow signals over simplicial complexes, extending classical least-mean-squares (LMS) methods to high-order topological domains. Building on discrete Hodge theory, we…

Signal Processing · Electrical Eng. & Systems 2025-05-30 Lorenzo Marinucci , Claudio Battiloro , Paolo Di Lorenzo

Orthogonal polynomials with respect to a weight function defined on a wedge in the plane are studied. A basis of orthogonal polynomials is explicitly constructed for two large class of weight functions and the convergence of Fourier…

Classical Analysis and ODEs · Mathematics 2018-07-06 Sheehan Olver , Yuan Xu

The strong-form asymmetric kernel-based collocation method, commonly referred to as the Kansa method, is easy to implement and hence is widely used for solving engineering problems and partial differential equations despite the lack of…

Numerical Analysis · Mathematics 2018-01-03 Ka-Chun Cheung , Leevan Ling , Robert Schaback

We propose the study of a conformally invariant functional for surfaces of complex projective plane which is closely related to the classical Willmore functional. We show that minimal surfaces of complex projective plane are critical for…

Differential Geometry · Mathematics 2007-05-23 Sebastian Montiel , Francisco Urbano

We introduce a simple diagnostic test for assessing the overall or partial goodness of fit of a linear causal model with errors being independent of the covariates. In particular, we consider situations where hidden confounding is…

Methodology · Statistics 2023-03-06 Christoph Schultheiss , Peter Bühlmann , Ming Yuan