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It recently has been found that methods of the statistical theories of spectra can be a useful tool in the analysis of spectra far from levels of Hamiltonian systems. Several examples originate from areas, such as quantitative linguistics…

Statistical Mechanics · Physics 2020-05-26 Rongrong Xie , Weibing Deng , Mauricio P. Pato

For data sets with similar features, for example highly correlated features, most existing stability measures behave in an undesired way: They consider features that are almost identical but have different identifiers as different features.…

Machine Learning · Statistics 2021-01-18 Andrea Bommert , Jörg Rahnenführer

It has been suggested that space-time might undergo fluctuations because of its intrinsic quantum nature. These fluctuations would pose a fundamental limit to the ability of measuring distances with arbitrary precision, beyond any…

General Relativity and Quantum Cosmology · Physics 2009-11-10 S. Schiller , C. Laemmerzahl , H. Mueller , C. Braxmaier , S. Herrmann , A. Peters

Suppose (standardized) measurements or statistics are monitored to raise an alarm when a threshold is exceeded. Often, the underlying population is heterogenous with respect to important discrete variables and thus samples may consist of…

Statistics Theory · Mathematics 2025-10-10 Ansgar Steland

This paper investigates calibration of sensor arrays in the radio astronomy context. Current and future radio telescopes require computationally efficient algorithms to overcome the new technical challenges as large collecting area, wide…

Applications · Statistics 2018-07-31 Virginie Ollier , Mohammed Nabil El Korso , André Ferrari , Rémy Boyer , Pascal Larzabal

Recent research has shown that interval estimators with good coverage properties are achievable for some functions of quantiles, even when sample sizes are not large. Motivated by this, we consider interval estimators for the ratios of…

Statistics Theory · Mathematics 2019-05-21 Chandima N. P. G. Arachchige , Maxwell Cairns , Luke A. Prendergast

Traditional statistical inference considers relatively small data sets and the corresponding theoretical analysis focuses on the asymptotic behavior of a statistical estimator when the number of samples approaches infinity. However, many…

Methodology · Statistics 2013-01-03 Jon Wellner , Tong Zhang

This paper develops change-point methods for the spectrum of a locally stationary time series. We focus on series with a bounded spectral density that change smoothly under the null hypothesis but exhibits change-points or becomes less…

Statistics Theory · Mathematics 2024-08-08 Alessandro Casini , Pierre Perron

The canonical range resolution limit in radar, sonar, and lidar systems is found to be a special case of a more general resolution limit. The general limit indicates that it is possible to surpass the canonical limit in moderate (of order…

Applied Physics · Physics 2025-03-20 Nathaniel J. Fuller , Nicholas Palermo

Fermi's golden rule (FGR) serves as the basis for many expressions of spectroscopic observables and quantum transition rates. The utility of FGR has been demonstrated through decades of experimental confirmation. However, there still remain…

Quantum Physics · Physics 2025-12-30 Seogjoo J. Jang , Young Min Rhee

We establish the limiting spectral distribution of Kendall's correlation matrices in the moderate high-dimensional regime where the dimension grows slower than the sample size. Our framework allows observations to be independent but not…

Statistics Theory · Mathematics 2026-03-10 Raunak Shevade , Monika Bhattacharjee

We adapt Higher Criticism (HC) to the comparison of two frequency tables which may -- or may not -- exhibit moderate differences between the tables in some unknown, relatively small subset out of a large number of categories. Our analysis…

Statistics Theory · Mathematics 2023-08-29 David L. Donoho , Alon Kipnis

A new, computationally- and statistically-efficient algorithm, the Fast $\chi^2$ algorithm, can find a periodic signal with harmonic content in irregularly-sampled data with non-uniform errors. The algorithm calculates the minimized…

Data Analysis, Statistics and Probability · Physics 2009-04-17 David M. Palmer

This paper considers estimation of a univariate density from an individual numerical sequence. It is assumed that (i) the limiting relative frequencies of the numerical sequence are governed by an unknown density, and (ii) there is a known…

Probability · Mathematics 2008-06-19 Andrew B. Nobel , Gusztav Morvai , Sanjeev R. Kulkarni

Limited overlap between treated and control groups is a key challenge in observational analysis. Standard approaches like trimming importance weights can reduce variance but introduce a fundamental bias. We propose a sensitivity framework…

Machine Learning · Statistics 2026-04-21 Yuanzhe Ma , Yian Huang , Hongseok Namkoong

An analytical relationship between the statistical significance of an observed signal and the signal width in case of a large background was obtained. It can help to explain why high-energy experiments may have different conclusions on the…

High Energy Physics - Phenomenology · Physics 2009-06-22 S. V. Chekanov , B. B. Levchenko

We develop a method to generate prediction intervals that have a user-specified coverage level across all regions of feature-space, a property called conditional coverage. A typical approach to this task is to estimate the conditional…

Machine Learning · Computer Science 2021-10-05 Shai Feldman , Stephen Bates , Yaniv Romano

The low frequency region of the spectrum is a challenging regime for quantum probes. We support the idea that, in this regime, performing Ramsey measurements carefully controlling the time at which each measurement is initiated is an…

Quantum Physics · Physics 2024-05-28 Santiago Oviedo-Casado , Javier Prior , Javier Cerrillo

Fast-sampled models are essential for control design, e.g., to address intersample behavior. The aim of this paper is to develop a non-parametric identification technique for fast-sampled models of systems that have relevant dynamics and…

Systems and Control · Electrical Eng. & Systems 2023-06-08 Max van Haren , Leonid Mirkin , Lennart Blanken , Tom Oomen

Detection of periodic patterns of interest within noisy time series data plays a critical role in various tasks, spanning from health monitoring to behavior analysis. Existing learning techniques often rely on labels or clean versions of…

Machine Learning · Computer Science 2025-06-24 Berken Utku Demirel , Christian Holz
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