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Fabrication process variations are a major source of yield degradation in the nano-scale design of integrated circuits (IC), microelectromechanical systems (MEMS) and photonic circuits. Stochastic spectral methods are a promising technique…

Computational Engineering, Finance, and Science · Computer Science 2016-11-08 Zheng Zhang , Tsui-Wei Weng , Luca Daniel

Particle suspensions, present in many natural and industrial settings, typically contain aggregates or other microstructures that can complicate macroscopic flow behaviors and damage processing equipment. Recent work found that applying…

Soft Condensed Matter · Physics 2018-07-31 Jikai Wang , J. M. Schwarz , Joseph D. Paulsen

Measurement system analysis aims to quantify the variability in data attributable to the measurement system and evaluate its contribution to overall data variability. This paper conducts a rigorous theoretical investigation of the…

Applications · Statistics 2025-01-31 Banafsheh Lashkari , Shojaeddin Chenouri

The spectrum and coherency are useful quantities for characterizing the temporal correlations and functional relations within and between point processes. This paper begins with a review of these quantities, their interpretation and how…

Biological Physics · Physics 2007-05-23 M. R. Jarvis , P. P. Mitra

The microstructure critically governs the properties of materials used in energy and chemical engineering technologies, from catalysts and filters to thermal insulators and sensors. Therefore, accurate design is based on quantitative…

Computational Engineering, Finance, and Science · Computer Science 2026-01-29 Maksym Szemer , Szymon Buchaniec , Grzegorz Brus

Biological and physical systems often exhibit distinct structures at different spatial/temporal scales. Persistent homology is an algebraic tool that provides a mathematical framework for analyzing the multi-scale structures frequently…

Algebraic Topology · Mathematics 2016-02-01 Jonathan Jaquette , Miroslav Kramár

As an important physical quantity to understand the internal structure of polymer chains, the structure factor is being studied both in theory and experiment. Theoretically, the structure factor of Gaussian chains have been solved…

Soft Condensed Matter · Physics 2021-04-21 Jie Huang , Xinghua Zhang , Gang Huang , Shiben Li

This paper considers a structural-factor approach to modeling high-dimensional time series and space-time data by decomposing individual series into trend, seasonal, and irregular components. For ease in analyzing many time series, we…

Methodology · Statistics 2019-03-19 Zhaoxing Gao , Ruey S Tsay

When the experimental data set is contaminated, we usually employ robust alternatives to common location and scale estimators such as the sample median and Hodges-Lehmann estimators for location and the sample median absolute deviation and…

Methodology · Statistics 2020-08-11 Chanseok Park , Haewon Kim , Min Wang

Qualitative methods such as the linear sampling method and the factorization method reconstruct acoustic scatterers through sampling indicators. In practice, these indicators are gray-scale fields on a prescribed sampling window and a…

Numerical Analysis · Mathematics 2026-05-21 Xiaomei Yang , Jiaying Jia , Zhiliang Deng

Consider a real-valued function that can only be observed with stochastic noise at a finite set of design points within a Euclidean space. We wish to determine whether there exists a convex function that goes through the true function…

Other Statistics · Statistics 2018-07-30 Nanjing Jian , Shane G. Henderson

In this paper, we propose a new comparison tool for spatial homogeneity of point processes, based on the joint examination of void probabilities and factorial moment measures. We prove that determinantal and permanental processes, as well…

Probability · Mathematics 2014-04-23 Bartlomiej Blaszczyszyn , D. Yogeshwaran

We formalize notions of robustness for composite estimators via the notion of a breakdown point. A composite estimator successively applies two (or more) estimators: on data decomposed into disjoint parts, it applies the first estimator on…

Machine Learning · Computer Science 2016-09-06 Pingfan Tang , Jeff M. Phillips

Modern multiscale type segmentation methods are known to detect multiple change-points with high statistical accuracy, while allowing for fast computation. Underpinning theory has been developed mainly for models that assume the signal as a…

Statistics Theory · Mathematics 2019-09-26 Housen Li , Qinghai Guo , Axel Munk

Due to the complexity of order statistics, the finite sample behaviour of robust statistics is generally not analytically solvable. While the Monte Carlo method can provide approximate solutions, its convergence rate is typically very slow,…

Methodology · Statistics 2024-09-12 Li Tuobang

The scaling behaviour of the diffraction intensity near the origin is investigated for (partially) ordered systems, with an emphasis on illustrative, rigorous results. This is an established method to detect and quantify the fluctuation…

Metric Geometry · Mathematics 2021-06-15 Michael Baake , Uwe Grimm

We provide a unified approach to a method of estimation of the regression parameter in balanced linear models with a structured covariance matrix that combines a high breakdown point and bounded influence with high asymptotic efficiency at…

Statistics Theory · Mathematics 2023-03-22 Hendrik Paul Lopuhaä

For a sample of Exponentially distributed durations we aim at point estimation and a confidence interval for its parameter. A duration is only observed if it has ended within a certain time interval, determined by a Uniform distribution.…

Methodology · Statistics 2021-10-19 Rafael Weißbach , Dominik Wied

The hyperuniformity concept provides a unified means to classify all perfect crystals, perfect quasicrystals, and exotic amorphous states of matter according to their capacity to suppress large-scale density fluctuations. While the…

Statistical Mechanics · Physics 2021-01-27 Jaeuk Kim , Salvatore Torquato

We show how information on the uniformity properties of a point set employed in numerical multidimensional integration can be used to improve the error estimate over the usual Monte Carlo one. We introduce a new measure of (non-)uniformity…

High Energy Physics - Phenomenology · Physics 2009-10-28 Jiri Hoogland , Ronald Kleiss