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050	0	0	_aQA274.7 _b.M355 1998
082	0	0	_a519.233 _221
245	0	0	_aMarkov chain Monte Carlo in practice / _cedited by W.R. Gilks, S. Richardson, and D.J. Spiegelhalter.
264		1	_aBoca Raton, Fla. : _bChapman & Hall, _c1998.
300			_axvii, 486 pages : _billustrations ; _c25 cm
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
500			_aPreviously published: London : Chapman & Hall, 1996.
504			_aIncludes bibliographical references and index.
505	0		_aIntroducing Markov chain Monte Carlo / W.R. Gilks, S. Richardson and D.J. Spiegelhalter -- Hepatitis B : a case study in MCMC methods / D.J. Spiegelhalter ... [et al.] -- Markov chain concepts related to sampling algorithms / G.O. Roberts -- Introduction to general state-space Markov chain theory / L. Tierney -- Full conditional distributions / W.R. Gilks -- Strategies for improving MCMC / W.R. Gilks and G.O. Roberts -- Implementing MCMC / A.E. Raftery and S.M. Lewis -- Inference and monitoring convergence / A. Gelman -- Model determination using sampling-based methods / A.E. Gelfand -- Hypothesis testing and model selection / A.E. Raftery -- Model checking and model improvement / A. Gelman and X.-L. Meng -- Stochastic search variable selection / E.I. George and R.E. McCulloch -- Bayesian model comparison via jump diffusions / D.B. Phillips and A.F.M. Smith -- Estimation and optimization of functions / C.J. Geyer -- Stochastic EM : method and application / J. Diebolt and E.H.S. Ip -- Generalized linear mixed models / D.G. Clayton -- Hierarchical longitudinal modeling / B.P. Carlin -- Medical monitoring / C. Berzuini -- MCMC for nonlinear hierarchical models / J.E. Bennett, A. Racine-Poon and J.C. Wakefield -- Bayesian mapping of disease / A. Mollié -- MCMC in image analysis / P.J. Green -- Measurement error / S. Richardson -- Gibbs sampling methods in genetics / D.C. Thomas and W.J. Gauderman -- Mixtures of distributions : inference and estimation / C.P. Robert -- An archaeological example : radiocarbon dating / C. Litton and C. Buck.
520			_a"General state-space Markov chain theory has evolved to make it both more accessible and more powerful. Markov Chain Monte Carlo in Practice introduces MCMC methods and their applications while also providing some theoretical background. Considering the broad audience, the editors emphasize practice rather than theory and keep the technical content to a minimum. They offer step-by-step instructions for using the methods presented and show the importance of MCMC in real applications with examples ranging from the simple to the more complex in fields such as archaeology, astronomy, biostatistics, genetics, epidemiology, and image analysis."--Publisher description.
588			_aMachine converted from AACR2 source record.
650		0	_aMarkov processes _9320449
650		0	_aMonte Carlo method. _9321027
650		0	_aMedical statistics _9320649
650		0	_aBiometry. _9314584
700	1		_aGilks, W. R. _q(Walter R.), _eeditor. _9256947
700	1		_aRichardson, S. _q(Sylvia), _eeditor. _9272648
700	1		_aSpiegelhalter, D. J., _eeditor. _9272544
907			_a.b10971713 _b26-03-18 _c27-10-15
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