• Bayes in the sky : Bayesian in...

Treffer: Bayes in the sky : Bayesian inference and model selection in cosmology

Title:
Bayes in the sky : Bayesian inference and model selection in cosmology
Authors:
TROTTA, Roberto
Source:
Contemporary physics. 49(2):71-104
Publisher Information:
London: Taylor & Francis, 2008.
Publication Year:
2008
Physical Description:
print, 112 ref
Original Material:
INIST-CNRS
Subject Terms:
Physics, Physique, Sciences exactes et technologie, Exact sciences and technology, Terre, ocean, espace, Earth, ocean, space, Astronomie, Astronomy, Astronomie fondamentale et astrophysique. Instrumentation, techniques, et observations astronomiques, Fundamental astronomy and astrophysics. Instrumentation, techniques, and astronomical observations, Techniques d'observation et de réduction des données. Simulation et modélisation par ordinateur, Observation and data reduction techniques. Computer modeling and simulation, Méthodes mathématiques et méthodes de simulation sur ordinateur, Mathematical procedures and computer techniques, Systèmes stellaires. Objets et systèmes galactiques et extragalactiques. L'univers, Stellar systems. Galactic and extragalactic objects and systems. The universe, Cosmologie, Cosmology, Cosmologie mathématique et relativiste. Cosmologie quantique, Mathematical and relativistic aspects of cosmology. Quantum cosmology, Chaîne Markov, Markov chain, Cadena Markov, Complexité, Complexity, Complejidad, Cosmologie, Cosmology, Incertitude, Uncertainty, Incertidumbre, Modèle cosmologique, Cosmological models, Modèle théorique, Theoretical model, Modelo teórico, Méthode Bayes, Bayes methods, Paramètre cosmologique, Cosmological parameter, Parámetro cosmológico, Théorie probabilité, Probability theory, Teoría probabilidad
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Astrophysics Department, Oxford University, Oxford, United Kingdom
ISSN:
0010-7514
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=20505726
Rights:
Copyright 2008 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Astronomy
Accession Number:
edscal.20505726
Database:
PASCAL Archive

Weitere Informationen

The application of Bayesian methods in cosmology and astrophysics has flourished over the past decade, spurred by data sets of increasing size and complexity. In many respects, Bayesian methods have proven to be vastly superior to more traditional statistical tools, offering the advantage of higher efficiency and of a consistent conceptual basis for dealing with the problem of induction in the presence of uncertainty. This trend is likely to continue in the future, when the way we collect, manipulate and analyse observations and compare them with theoretical models will assume an even more central role in cosmology. This review is an introduction to Bayesian methods in cosmology and astrophysics and recent results in the field. I first present Bayesian probability theory and its conceptual underpinnings, Bayes' Theorem and the role of priors. I discuss the problem of parameter inference and its general solution, along with numerical techniques such as Monte Carlo Markov Chain methods. I then review the theory and application of Bayesian model comparison, discussing the notions of Bayesian evidence and effective model complexity, and how to compute and interpret those quantities. Recent developments in cosmological parameter extraction and Bayesian cosmological model building are summarised, highlighting the challenges that lie ahead.