000			01644 a2200229 4500
005			20190114145555.0
008			190104b xxu||||| |||| 00| 0 eng d
020			_a9781107102132
040			_cIIT Kanpur
041			_aeng
082			_a523.0101 _bB341
245			_aBayesian astrophysics _cedited by Andres Asensio Ramos and Ingio Arregui
260			_bCambridge University Press _c2018 _aNew York
300			_axiii, 194p
440			_aCanary islands winter school of astrophysics
490			_a/ edited by Rafael Rebolo; v. 26
520			_aBayesian methods are being increasingly employed in many different areas of research in the physical sciences. In astrophysics, models are used to make predictions to be compared to observations. These observations offer information that is incomplete and uncertain, so the comparison has to be pursued by following a probabilistic approach. With contributions from leading experts, this volume covers the foundations of Bayesian inference, a description of computational methods, and recent results from their application to areas such as exoplanet detection and characterisation, image reconstruction, and cosmology. It appeals to both young researchers seeking to learn about Bayesian methods as well as to astronomers wishing to incorporate these approaches in their research areas. It provides the next generation of researchers with the tools of modern data analysis that are already becoming standard in current astrophysical research.
650			_aBayesian statistical decision theory
700			_aRamos, Andres Asensio [ed.]
700			_aArregui, Inigo [ed.]
942			_cBK
999			_c559956 _d559956