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Related papers: A practical guide to measuring the Hurst parameter

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The objective of the current study is to utilize an innovative method called 'change probabilities' for describing fracture roughness. In order to detect and visualize anisotropy of rock joint surfaces, the roughness of one-dimensional…

Statistics Theory · Mathematics 2021-12-23 Tim Gutjahr , Sina Hale , Karsten Keller , Philipp Blum , Steffen Winter

Efficient methods for characterizing the performance of quantum measurements are important in the experimental quantum sciences. Ideally, one requires both a physically relevant distinguishability measure between measurement operations and…

Quantum Physics · Physics 2015-06-12 Easwar Magesan , Paola Cappellaro

In this paper we investigate the question of how much combined measurements can increase the accuracy of additive quantities. Therefore, we consider a set of measurements from a selection of all possible combinations of the $n$ labeled…

Data Analysis, Statistics and Probability · Physics 2022-05-18 B. Mirbach , M. Boguslawski

In this paper, we establish sharp upper and lower bounds on the convergence rate of the empirical measures of point processes under the Wasserstein distance. To this end, we first introduce a new metric on the space of counting measures…

Statistics Theory · Mathematics 2026-04-28 Dongzhou Huang , Tianyi Jiang , Haonan Wang

Fitting a simplifying model with several parameters to real data of complex objects is a highly nontrivial task, but enables the possibility to get insights into the objects physics. Here, we present a method to infer the parameters of the…

Data Analysis, Statistics and Probability · Physics 2018-12-21 Johannes Oberpriller , T. A. Enßlin

A model of quantum measurement is proposed, which aims to describe statistical mechanical aspects of this phenomenon, starting from a purely Hamiltonian formulation. The macroscopic measurement apparatus is modeled as an ideal Bose gas, the…

Statistical Mechanics · Physics 2016-08-31 Armen E. Allahverdyan , Roger Balian , Theo M. Nieuwenhuizen

Simulation studies are computer experiments that involve creating data by pseudorandom sampling. The key strength of simulation studies is the ability to understand the behaviour of statistical methods because some 'truth' (usually some…

Methodology · Statistics 2019-01-18 Tim P Morris , Ian R White , Michael J Crowther

This paper describes how a priori information about the signal parameters can influence the accuracy of estimating the number of these signals. This study considers sinusoidal signals and it is supposed that the parameters (amplitudes,…

Signal Processing · Electrical Eng. & Systems 2020-09-03 Aleksandr Kharin , Oleg V. Chernoyarov

Precision control of a quantum system requires accurate determination of the effective system Hamiltonian. We develop a method for estimating the Hamiltonian parameters for some unknown two-state system and providing uncertainty bounds on…

Honeypots are a deceptive technology used to capture malicious activity. The technology is useful for studying attacker behavior, tools, and techniques but can be difficult to implement and maintain. Historically, a lack of measures of…

Cryptography and Security · Computer Science 2020-11-03 Jason M. Pittman , Kyle Hoffpauir , Nathan Markle

I present a frequentist method for quantifying uncertainty when correcting correlations for attenuation due to measurement error. The method is conservative but has far better coverage properties than the methods currently used when sample…

Methodology · Statistics 2019-11-06 Jonas Moss

Data analysis is a powerful tool in all experimental sciences. Statistical methods, such as sampling theory, computer technologies necessary for handling large amounts of data, skill in analysing information contained in different types of…

Physics Education · Physics 2012-06-20 Vera Montalbano

This paper describes privacy-preserving approaches for the statistical analysis. It describes motivations for privacy-preserving approaches for the statistical analysis of sensitive data, presents examples of use cases where such methods…

Different ways of extracting parameters of interest from combined data sets of separate experiments are investigated accounting for the systematic errors. It is shown, that the frequentist approach may yield larger $\chi^2$ values when…

High Energy Physics - Experiment · Physics 2018-04-17 R. Orava , O. V. Selyugin

In this contribution I review rigorous formulations of a variety of limitations of measurability in quantum mechanics. To this end I begin with a brief presentation of the conceptual tools of modern measurement theory. I will make precise…

Quantum Physics · Physics 2011-01-04 Paul Busch

The purpose of this article is to introduce a new analytical framework dedicated to measuring performance of recommender systems. The standard approach is to assess the quality of a system by means of accuracy related statistics. However,…

Artificial Intelligence · Computer Science 2010-10-29 Szymon Chojnacki , Mieczysław Kłopotek

The varied landscape of robotic hand designs makes it difficult to set a standard for how to measure hand size and to communicate the size of objects it can grasp. Defining consistent workspace measurements would greatly assist scientific…

Robotics · Computer Science 2021-06-22 John Morrow , Nuha Nishat , Joshua Campbell , Ravi Balasubramanian , Cindy Grimm

New concepts of rough natural number systems, recently introduced by the present author, are used to improve most rough set-theoretical measures in general Rough Set theory (\textsf{RST}) and measures of mutual consistency of multiple…

Logic · Mathematics 2011-02-15 A. Mani

Physical theories that depend on many parameters or are tested against data from many different experiments pose unique challenges to statistical inference. Many models in particle physics, astrophysics and cosmology fall into one or both…

The Hurst exponent is the simplest numerical summary of self-similar long-range dependent stochastic processes. We consider the estimation of Hurst exponent in long-range dependent curve time series. Our estimation method begins by…

Statistics Theory · Mathematics 2020-09-21 Han Lin Shang