000			03080nam a22003978i 4500
001			CR9781139565608
005			20250919142046.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			120719s2014||||enk o ||1 0|eng|d
020			_a9781139565608 (ebook)
020			_z9781107035904 (hardback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aQC174.85.P76 _bL56 2014
082	0	0	_a519.5/42 _223
100	1		_aLinden, Wolfgang von der, _eauthor.
245	1	0	_aBayesian probability theory : _bapplications in the physical sciences / _cWolfgang von der Linden, Graz University of Technology, Institute for Theoretical and Computational Physics, Graz, Austria, Volker Dose, Max Planck Institute for Plasma Physics, Garching, Germany, Udo von Toussaint, Max Planck Institute for Plasma Physics, Garching, Germany.
264		1	_aCambridge : _bCambridge University Press, _c2014.
300			_a1 online resource (xiii, 637 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
500			_aTitle from publisher's bibliographic system (viewed on 01 Feb 2016).
505	0		_aThe meaning of probability -- Basic definitions -- Bayesian inference -- Combinatrics -- Random walks -- Limit theorems -- Continuous distributions -- The central limit theorem -- Poisson processes and waiting times -- Transformation invariance -- Maximum entropy -- Qualified maximum entropy -- Global smoothness -- Bayesian parameter estimation -- Frequentist parameter estimation -- The Cramer-Rao inequality -- The Bayesian way -- The frequentist way -- Sampling distributions -- Bayesian vs frequentist hypothesis tests -- Regression -- Inconsistent data -- Unrecognized signal contributions -- Change point problems -- Function estimation -- Integral equations -- Model selection -- Bayesian experimental design -- Numerical integration -- Monte Carlo methods -- Nested sampling.
520			_aFrom the basics to the forefront of modern research, this book presents all aspects of probability theory, statistics and data analysis from a Bayesian perspective for physicists and engineers. The book presents the roots, applications and numerical implementation of probability theory, and covers advanced topics such as maximum entropy distributions, stochastic processes, parameter estimation, model selection, hypothesis testing and experimental design. In addition, it explores state-of-the art numerical techniques required to solve demanding real-world problems. The book is ideal for students and researchers in physical sciences and engineering.
650		0	_aProbabilities.
650		0	_aBayesian statistical decision theory.
700	1		_aDose, Volker, _eauthor.
700	1		_aToussaint, Udo von, _eauthor.
776	0	8	_iPrint version: _z9781107035904
856	4	0	_uhttps://doi.org/10.1017/CBO9781139565608
907			_a.b16846126 _b2020-12-22 _c2020-12-22
942			_n0
998			_a1 _b2020-12-22 _cm _da _feng _genk _y0 _z.b16846126
999			_c651955 _d651955