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In recent years cosmologists have advanced from largely qualitative models of the Universe to precision modelling using Bayesian methods, in order to determine the properties of the Universe to high accuracy. This timely book is the only comprehensive introduction to the use of Bayesian methods in cosmological studies, and is an essential reference for graduate students and researchers in cosmology, astrophysics and applied statistics. The first part of the book focuses on methodology, setting the basic foundations and giving a detailed description of techniques. It covers topics including the…mehr

Produktbeschreibung
In recent years cosmologists have advanced from largely qualitative models of the Universe to precision modelling using Bayesian methods, in order to determine the properties of the Universe to high accuracy. This timely book is the only comprehensive introduction to the use of Bayesian methods in cosmological studies, and is an essential reference for graduate students and researchers in cosmology, astrophysics and applied statistics. The first part of the book focuses on methodology, setting the basic foundations and giving a detailed description of techniques. It covers topics including the estimation of parameters, Bayesian model comparison, and separation of signals. The second part explores a diverse range of applications, from the detection of astronomical sources (including through gravitational waves), to cosmic microwave background analysis and the quantification and classification of galaxy properties. Contributions from 24 highly regarded cosmologists and statisticians make this an authoritative guide to the subject.

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Autorenporträt
John Skilling, D. S. Sivia, Steve Rawlings, Antony Lewis, Sarah Bridle, Andrew R. Liddle, Pia Mukherjee, David Parkinson, Roberto Trotta, Martin Kunz, M. P. Hobson, M. A. J. Ashdown, V. Stolyarov, Graça Rocha, R. Savage, Daniel Mortlock, Neil Cornish, Andrew H. Jaffe, Thomas J. Loredo, Martin A. Hendry, Stefano Andreon, Ofer Lahav, Filipe B. Abdalla, Manda Banerji