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In \cite{liu2022practical}, a general algorithm is developed to efficiently obtain the best accuracy using the regular refinement. The adaptive refinement allows for obtaining an accuracy with a smaller number of DoFs compared with the…

Numerical Analysis · Mathematics 2025-03-25 Jie Liu

The distance between the true and numerical solutions in some metric is considered as the discretization error magnitude. If error magnitude ranging is known, the triangle inequality enables the estimation of the vicinity of the approximate…

Computational Physics · Physics 2018-05-11 A. K. Alekseev , A. E. Bondarev , I. M. Navon

Analysis of a probabilistic system often requires to learn the joint probability distribution of its random variables. The computation of the exact distribution is usually an exhaustive precise analysis on all executions of the system. To…

Information Theory · Computer Science 2023-07-19 Fabrizio Biondi , Yusuke Kawamoto , Axel Legay , Louis-Marie Traonouez

This work introduces an adaptive mesh refinement technique for hierarchical hybrid grids with the goal to reach scalability and maintain excellent performance on massively parallel computer systems. On the block structured hierarchical…

Numerical Analysis · Mathematics 2025-08-11 Benjamin Mann , Ulrich Rüde

This short note introduces the harmonic indel distance (HID), a new distance between strings where the cost of an insertion or deletion is inversely proportional to the string length. We present a closed-form formula and show that the HID…

Discrete Mathematics · Computer Science 2024-12-13 Bob Pepin

The sample mean is often used to aggregate different unbiased estimates of a parameter, producing a final estimate that is unbiased but possibly high-variance. This paper introduces the Bayesian median of means, an aggregation rule that…

Statistics Theory · Mathematics 2019-06-05 Paulo Orenstein

Towards understanding the fundamental limits of estimation from data of varied quality, we study the problem of estimating a mean parameter from heteroskedastic Gaussian observations where the variances are unknown and may vary arbitrarily…

Statistics Theory · Mathematics 2026-03-17 Yanjun Han , Abhishek Shetty , Jacob Shkrob

We obtain non-symmetric upper and lower bounds on the rate of convergence of general monotone approximation/numerical schemes for parabolic Hamilton Jacobi Bellman Equations by introducing a new notion of consistency. We apply our general…

Analysis of PDEs · Mathematics 2009-11-11 Guy Barles , Espen R. Jakobsen

Measurement error is a pervasive challenge across many disciplines, yet its impact on sample size determination and the accuracy and precision of estimators regarding the association between an exposure and an outcome remains understudied…

Methodology · Statistics 2025-05-27 Honghyok Kim

The goal of this paper is to explore the basic Approximate Bayesian Computation (ABC) algorithm via the lens of information theory. ABC is a widely used algorithm in cases where the likelihood of the data is hard to work with or…

Methodology · Statistics 2019-08-14 Konstantinos Spiliopoulos

We present a new set of accurate formulae for the computation of random errors in the measurement of atomic and molecular indices. The new expressions are in excellent agreement with numerical simulations. We have found that, in some cases,…

Astrophysics · Physics 2009-10-30 N. Cardiel , J. Gorgas , J. Cenarro , J. J. Gonzalez

Computer models are commonly used to represent a wide range of real systems, but they often involve some unknown parameters. Estimating the parameters by collecting physical data becomes essential in many scientific fields, ranging from…

Applications · Statistics 2020-05-27 Chih-Li Sung , Beau David Barber , Berkley J. Walker

The purpose of this paper is to analyze the isoperimetric inequality for symmetric log-convex probability measures on the line. Using geometric arguments we first re-prove that extremal sets in the isoperimetric inequality are intervals or…

Differential Geometry · Mathematics 2014-01-06 F. Feo , M. R. Posteraro , C. Roberto

The problem of developing an adaptive isogeometric method (AIGM) for solving elliptic second-order partial differential equations with truncated hierarchical B-splines of arbitrary degree and different order of continuity is addressed. The…

Numerical Analysis · Mathematics 2015-04-21 Annalisa Buffa , Carlotta Giannelli

STEP (the Satellite Test of the Equivalence Principle) will advance experimental limits on violations of Einstein's equivalence principle (EP) from their present sensitivity of 2 parts in 10^13 to 1 part in 10^18 through multiple comparison…

General Relativity and Quantum Cosmology · Physics 2014-01-21 James Overduin , Francis Everitt , John Mester , Paul Worden

This paper presents an $O(\log\log \bar{d})$ round massively parallel algorithm for $1+\epsilon$ approximation of maximum weighted $b$-matchings, using near-linear memory per machine. Here $\bar{d}$ denotes the average degree in the graph…

Data Structures and Algorithms · Computer Science 2022-11-16 Mohsen Ghaffari , Christoph Grunau , Slobodan Mitrović

Many randomized approximation algorithms operate by giving a procedure for simulating a random variable $X$ which has mean $\mu$ equal to the target answer, and a relative standard deviation bounded above by a known constant $c$. Examples…

Computation · Statistics 2019-08-16 Mark Huber

We mechanize the fundamental properties of a rounding error model for floating-point arithmetic based on relative precision, a measure of error proposed as a substitute for relative error in rounding error analysis. A key property of…

Numerical Analysis · Mathematics 2025-10-16 Max Fan , Ariel E. Kellison , Samuel D. Pollard

We investigate the representation of homogeneous, symmetric means in the form M(x,y)=\frac{x-y}{2f((x-y)/(x+y))}. This allows for a new approach to comparing means. As an example, we provide optimal estimate of the form (1-\mu)min(x,y)+ \mu…

Classical Analysis and ODEs · Mathematics 2018-01-08 Alfred Witkowski

We propose a Bayesian meta-analysis to infer the current expansion rate of the Universe, called the Hubble constant ($H_0$), via time delay cosmography. Inputs of the meta-analysis are estimates of two properties for each pair of…

Applications · Statistics 2024-11-14 Hyungsuk Tak , Xuheng Ding