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Related papers: Bayesian and frequentist approaches to resonance s…

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When searching over a large parameter space for anomalies such as events, peaks, objects, or particles, there is a large probability that spurious signals with seemingly high significance will be found. This is known as the look-elsewhere…

Data Analysis, Statistics and Probability · Physics 2020-10-09 Adrian E. Bayer , Uros Seljak

The two statistical methods, namely the frequentist and the Bayesian methods, are both commonly used for probabilistic inference in many scientific situations. However, it is not straightforward to interpret the result of one approach in…

Data Analysis, Statistics and Probability · Physics 2023-09-01 Alan H. Guth , Mohammad Hossein Namjoo

While gravitational waves have not yet been measured directly, data analysis from detection experiments commonly includes an upper limit statement. Such upper limits may be derived via a frequentist or Bayesian approach; the theoretical…

Data Analysis, Statistics and Probability · Physics 2015-03-19 Christian Röver , Chris Messenger , Reinhard Prix

The model representing two independent Poisson processes, labelled as "signal" and "background" and both contributing at the same time to the total number of counted events, is considered from a Bayesian point of view. This is a widely used…

Data Analysis, Statistics and Probability · Physics 2012-01-16 Diego Casadei

We describe and use two different statistical approaches to try and detect low-frequency solar oscillations in Sun-as-a-star data: a frequentist approach and a Bayesian approach. We have used frequentist statistics to search contemporaneous…

Solar and Stellar Astrophysics · Physics 2015-05-18 A. -M. Broomhall , W. J. Chaplin , Y. Elsworth , T. Appourchaux , R. New

In many hypothesis testing applications, we have mixed priors, with well-motivated informative priors for some parameters but not for others. The Bayesian methodology uses the Bayes factor and is helpful for the informative priors, as it…

Data Analysis, Statistics and Probability · Physics 2022-10-05 Jakob Robnik , Uroš Seljak

In high-energy astrophysics, it is common practice to account for the background overlaid with the counts from the source of interest with the help of auxiliary measurements carried on by pointing off-source. In this "on/off" measurement,…

Instrumentation and Methods for Astrophysics · Physics 2014-12-12 Diego Casadei

Observational astrophysics consists of making inferences about the Universe by comparing data and models. The credible intervals placed on model parameters are often as important as the maximum a posteriori probability values, as the…

Instrumentation and Methods for Astrophysics · Physics 2021-12-15 Will J. Percival , Oliver Friedrich , Elena Sellentin , Alan Heavens

The objective Bayesian treatment of a model representing two independent Poisson processes, labelled as "signal" and "background" and both contributing additively to the total number of counted events, is considered. It is shown that the…

Data Analysis, Statistics and Probability · Physics 2015-04-16 Diego Casadei

Previous studies based on Bayesian methods have shown that the constraints on cosmological parameters from the Baryonic Oscillation Spectroscopic Survey (BOSS) full-shape data using the Effective Field Theory of Large Scale Structure…

Cosmology and Nongalactic Astrophysics · Physics 2023-09-11 Emil Brinch Holm , Laura Herold , Théo Simon , Elisa G. M. Ferreira , Steen Hannestad , Vivian Poulin , Thomas Tram

We study the application of a Bayesian method to extract relevant information from data for the case of a signal consisting of two or more decaying particles and its background. The method takes advantage of the dependence that exists in…

High Energy Physics - Phenomenology · Physics 2023-06-06 Ezequiel Alvarez

We propose a Bayesian approach to the problem of multi-reference alignment -- the recovery of signals from noisy, randomly shifted observations. While existing frequentist methods accurately recover the signal at arbitrarily low…

Signal Processing · Electrical Eng. & Systems 2025-10-15 Axel Janson , Joakim Andén

We develop a method to perform an untargeted Bayesian search for anisotropic gravitational-wave backgrounds that can efficiently and accurately reconstruct the background intensity map. Our method employs an analytic marginalization of the…

General Relativity and Quantum Cosmology · Physics 2023-09-06 Adrian Ka-Wai Chung , Nicolas Yunes

The search for gamma-ray counterparts to gravitational-wave events with the CALET Gamma-ray Burst Monitor (CGBM) requires accurate and robust background modeling. Previous CALET observing runs (O3 and O4) relied on averaged pre/post-event…

High Energy Astrophysical Phenomena · Physics 2025-11-20 Bisweswar Sen

This paper presents a study of the large-sample behavior of the posterior distribution of a structural parameter which is partially identified by moment inequalities. The posterior density is derived based on the limited information…

Statistics Theory · Mathematics 2010-01-13 Yuan Liao , Wenxin Jiang

To the frequentist who computes posteriors, not all priors are useful asymptotically: in this paper Schwartz's 1965 Kullback-Leibler condition is generalised to enable frequentist interpretation of convergence of posterior distributions…

Statistics Theory · Mathematics 2017-11-28 B. J. K. Kleijn

Bayesian analysis has become an indispensable tool across many different cosmological fields including the study of gravitational waves, the Cosmic Microwave Background and the 21-cm signal from the Cosmic Dawn among other phenomena. The…

Instrumentation and Methods for Astrophysics · Physics 2023-12-19 Harry T. J. Bevins , William J. Handley , Pablo Lemos , Peter H. Sims , Eloy de Lera Acedo , Anastasia Fialkov , Justin Alsing

This paper investigates the consistency of a posterior distribution in the single-measurement fractional Calder\'on problem with additive Gaussian noise. We consider a Bayesian framework with rescaled and Gaussian sieve priors, using a…

Statistics Theory · Mathematics 2025-11-17 Pu-Zhao Kow , Janne Nurminen , Jesse Railo

Like light, gravitational waves are gravitationally lensed by intervening massive astrophysical objects, such as galaxies, clusters, black holes, and stars, resulting in a variety of potentially observable gravitational-wave lensing…

A Bayesian approach is presented for detecting and characterising the signal from discrete objects embedded in a diffuse background. The approach centres around the evaluation of the posterior distribution for the parameters of the discrete…

Astrophysics · Physics 2009-11-07 M. P. Hobson , C. McLachlan
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