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Related papers: Unbiased Estimators for Correlation Measurements

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The most accurate method to combine measurement from different experiments is to build a combined likelihood function and use it to perform the desired inference. This is not always possible for various reasons, hence approximate methods…

Data Analysis, Statistics and Probability · Physics 2017-03-28 Luca Lista

We study ratio metrics in A/B testing at the presence of correlation among observations coming from the same user and provides practical guidance especially when two metrics contradict each other. We propose new estimating methods to…

Applications · Statistics 2020-07-24 Keyu Nie , Yinfei Kong , Ted Tao Yuan , Pauline Berry Burke

High-dimensional systems are an important frontier for photonic quantum correlation experiments. These correlation tests commonly prescribe measurements with many possible outcomes but they are often implemented through many individual…

Quantum Physics · Physics 2025-05-01 Armin Tavakoli , Roope Uola , Jef Pauwels

Existing metrics in competing risks survival analysis such as concordance and accuracy do not evaluate a model's ability to jointly predict the event type and the event time. To address these limitations, we propose a new metric, which we…

Methodology · Statistics 2019-08-20 Kartik Ahuja , Mihaela van der Schaar

We propose a new optimization framework for aleatoric uncertainty estimation in regression problems. Existing methods can quantify the error in the target estimation, but they tend to underestimate it. To obtain the predictive uncertainty…

Computer Vision and Pattern Recognition · Computer Science 2021-03-12 Takumi Kawashima , Qing Yu , Akari Asai , Daiki Ikami , Kiyoharu Aizawa

Observational studies of recurrent event rates are common in biomedical statistics. Broadly, the goal is to estimate differences in event rates under two treatments within a defined target population over a specified followup window.…

Methodology · Statistics 2024-11-13 Arman Oganisian , Anthony Girard , Jon A. Steingrimsson , Patience Moyo

We investigate the cosmological dependence and the constraining power of large-scale galaxy correlations, including all redshift-distortions, wide-angle, lensing and gravitational potential effects on linear scales. We analyze the…

Cosmology and Nongalactic Astrophysics · Physics 2016-05-25 Alvise Raccanelli , Francesco Montanari , Daniele Bertacca , Olivier Doré , Ruth Durrer

Upcoming and ongoing large area weak lensing surveys will also discover large samples of galaxy clusters. Accurate and precise masses of galaxy clusters are of major importance for cosmology, for example, in establishing well calibrated…

Cosmology and Nongalactic Astrophysics · Physics 2015-08-24 F. Köhlinger , H. Hoekstra , M. Eriksen

Random sampling is an essential tool in the processing and transmission of data. It is used to summarize data too large to store or manipulate and meet resource constraints on bandwidth or battery power. Estimators that are applied to the…

Databases · Computer Science 2015-03-19 Edith Cohen , Haim Kaplan

In physics, it is frequently needed to precisely measure the count rate of some process. Quite often one needs to account for electronics dead time, pile-up and other features of data acquisition system to avoid systematic shifts of the…

Instrumentation and Detectors · Physics 2019-06-06 Alexander Nozik

Model selection aims to identify a sufficiently well performing model that is possibly simpler than the most complex model among a pool of candidates. However, the decision-making process itself can inadvertently introduce non-negligible…

Methodology · Statistics 2024-08-08 Yann McLatchie , Aki Vehtari

Although a system is described by a well-known set of equations leading to a deterministic behavior, in the real world the value of a measurand obtained by an experiment will mostly scatter. Accordingly, an uncertainty is associated with…

Data Analysis, Statistics and Probability · Physics 2019-06-24 Markus Schiebl

We propose an information-theoretic bias measurement technique through a causal interpretation of spurious correlation, which is effective to identify the feature-level algorithmic bias by taking advantage of conditional mutual information.…

Machine Learning · Computer Science 2022-01-11 Seonguk Seo , Joon-Young Lee , Bohyung Han

The identification of anomalies is a critical component of operating complex, and possibly large-scale and geo-graphically distributed cyber-physical systems. While designing anomaly detectors, it is common to assume Gaussian noise models…

Systems and Control · Electrical Eng. & Systems 2021-11-15 Venkatraman Renganathan , Navid Hashemi , Justin Ruths , Tyler H. Summers

The related studies of two-particle correlations and event-by-event fluctuations have played important roles in the search for new physics through the experimental study of relativistic heavy ion collisions. We present a general method of…

Nuclear Experiment · Physics 2008-11-26 Michael Daugherity

A record is an entry in a time series that is larger or smaller than all previous entries. If the time series consists of independent, identically distributed random variables with a superimposed linear trend, record events are positively…

Data Analysis, Statistics and Probability · Physics 2015-05-30 J. Franke , G. Wergen , J. Krug

Very little attention has been paid to the comparison of efficiency between high accuracy statistical parsers. This paper proposes one machine-independent metric that is general enough to allow comparisons across very different parsing…

Computation and Language · Computer Science 2007-05-23 Brian Roark , Eugene Charniak

While investigating quantum correlations in atomic systems, we note that single measurements contain information about these correlations. Using a simple model of measurement -- analogous to the one used in quantum optics -- we show how to…

Soft Condensed Matter · Physics 2009-11-10 Radka Bach , Kazimierz Rzazewski

We are in an era of precision measurements at the Large Hadron Collider. The precision that can be achieved on some of those is limited however due to large systematic uncertainties. This paper introduces a new technique to reduce the total…

Data Analysis, Statistics and Probability · Physics 2019-07-03 Petra Van Mulders

Accurate camera calibration is a precondition for many computer vision applications. Calibration errors, such as wrong model assumptions or imprecise parameter estimation, can deteriorate a system's overall performance, making the reliable…

Computer Vision and Pattern Recognition · Computer Science 2021-07-29 Annika Hagemann , Moritz Knorr , Holger Janssen , Christoph Stiller