Calcul des probabilités by Paul Lévy PDF

By Paul Lévy

ISBN-10: 2876472317

ISBN-13: 9782876472310

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Biometrika, 82, 711–732. Green, P. (2001) A primer on Markov chain Monte Carlo. In O. Barndorff-Nielsen, D. Cox and C. Kluppelberg (eds), Complex Stochastic Systems, chapter 1, pp 1–62. Chapman and Hall, London, UK. Green, P. (2003) Trans-dimensional Markov Chain Monte Carlo. In P. Green, N. Hjort and S. Richardson (eds), Highly Structured Stochastic Systems, pp. 179–198. Oxford University Press, Oxford, UK. Griffin, J. and Stephens, D. (2013) Advances in Markov chain Monte Carlo. In P. Damien, P.

And Dey, D. (1994) Bayesian model choice: Asymptotics and exact calculations. Journal of the Royal Statistical Society B, 56(3), 501–514. Gelfand, A. and Ghosh, S. (1998) Model choice: A minimum posterior predictive loss approach. Biometrika, 85(1), 1–11. Gelfand, A. and Sahu, S. (1999) Identifiability, improper priors, and Gibbs sampling for generalized linear models. Journal of the American Statistical Association, 94, 247–253. Gelfand, A. and Smith, A. (1990) Sampling-based approaches to calculating marginal densities.

This provides J within-chain interval lengths, with mean IW . For the pooled output of (T − B)J samples, the same 100(1 − ????)% interval IP is also obtained. The ratio IP ∕IW converges to 1 under convergent mixing over chains. The analysis of sampled values from a single MCMC chain or parallel chains may be seen as an application of time series methods in regard to problems such as assessing stationarity in an autocorrelated sequence (Roberts, 1996). Thus the autocorrelation at lags 1, 2, and so on, may be assessed from the original series of sampled values ???? (t) , at lag 1 from the samples ???? (t+1) , ???? (t+2) … , or from more widely spaced sub-samples k steps apart ???? (t) , ???? (t+k) , ???? (t+2k) .

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Calcul des probabilités by Paul Lévy

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