Bayesian reasoning in data analysis
A critical introduction

by Giulio D'Agostini

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164

'http://www.bayesian.org/
http://www.amstat.org/sections/SBSS/
http://bayes.stat.washington.edu/bayes_people.html
http://www.ar-tiste.com/blip.html
http://www.strauss.lanl.gov/Welcome.html
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165

http://astrosun.tn.cornell.edu/staff/loredo/bayes/tjl.html

166

http://www.ipp.mpg.de/OP/Datenanalyse/ http://public.lanl.gov/kmh/publications/publications.html

167

Uncertainty Quantification Working Group, http://public.lanl.gov/ kmh/uncertainty/

168

A.F.M. Smith, ``Bayesian numerical analysis'', Phil. Trans. R. Soc. London 337 (1991) 369.

169

R.M. Neal, ``Probabilistic inference using Markov Chain Monte Carlo Methods'', Technical Report CRG-TR-93-1, University of Toronto, 1993, ftp://ftp.cs.utoront.ca/pub/radford/review.pdf.

170

W.R. Gilks, S. Richardson and D.J. Spiegelhalter ``Markov Chain Monte Carlo in practice'', Chapman and Hall, 1996.

171

R.E. Kass, B.P. Carlin, A. Gelman and R.M. Neal, ``Markov Chain Monte Carlo in practice: A roundtable discussion'', Am. Stat. 52 (1998) 93 [http://www.amstat.org/publications/tas/kass.pdf].

172

K.M. Hanson, ``Tutorial on Markov Chain Monte Carlo'', XX International Workshop on Maximum Entropy and Bayesian Methods in Science and Engineering, Gif-sur-Yvette (France), July 2000,

173

A. Lewis and S. Bridle, ``Cosmological parameters from CMB and other data: a Monte-Carlo approach'', Phys. Rev. D66 (2002) 103511 [astro-ph/0205436].

174

http://cerebro.xu.edu/math/Sources/.

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