Analyse bayésienne du modèle Logit : algorithme par tranches ou Metropolis-Hastings ?

Anas Altaleb; Christian P. Robert

Revue de Statistique Appliquée (2001)

  • Volume: 49, Issue: 4, page 53-70
  • ISSN: 0035-175X

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Altaleb, Anas, and Robert, Christian P.. "Analyse bayésienne du modèle Logit : algorithme par tranches ou Metropolis-Hastings ?." Revue de Statistique Appliquée 49.4 (2001): 53-70. <http://eudml.org/doc/106507>.

@article{Altaleb2001,
author = {Altaleb, Anas, Robert, Christian P.},
journal = {Revue de Statistique Appliquée},
language = {fre},
number = {4},
pages = {53-70},
publisher = {Société française de statistique},
title = {Analyse bayésienne du modèle Logit : algorithme par tranches ou Metropolis-Hastings ?},
url = {http://eudml.org/doc/106507},
volume = {49},
year = {2001},
}

TY - JOUR
AU - Altaleb, Anas
AU - Robert, Christian P.
TI - Analyse bayésienne du modèle Logit : algorithme par tranches ou Metropolis-Hastings ?
JO - Revue de Statistique Appliquée
PY - 2001
PB - Société française de statistique
VL - 49
IS - 4
SP - 53
EP - 70
LA - fre
UR - http://eudml.org/doc/106507
ER -

References

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  1. Besag, J. et Green, P.J. (1993) Spatial Statistics and Bayesian computation (avec discussion). Journal of the Royal Statistical Society (Series B) 55, 25-38. Zbl0800.62572MR1210422
  2. Best, N.G., Cowles, M.K. et Vines, K. (1995) CODA : Convergence diagnosis and output analysis software for Gibbs sampling output, Version 0.30. Tech. Report, MRC Biostatistics Unit, Univ. of Cambridge. 
  3. Brooks S.P. et Roberts, G. (1998) Assessing convergence of Markov chain Monte Carlo algorithms. Statistics and Computing8, 319-335. 
  4. Carlin, B.P. et Chib, S. (1995) Bayesian model choice through Markov-Chain Monte Carlo. Journal of the Royal Statistical Society (Series B), 57, 473-484. Zbl0827.62027
  5. Cowles, M.K. et Carlin, B.P. (1996) Markov Chain Monte Carlo convergence diagnostics : a comparative study. Journal of the American Statistical Association91, 883-904. Zbl0869.62066MR1395755
  6. Damien, P. et Walker, S. (1996) Sampling probability densities via uniform random variables and a Gibbs sampler. Tech. Report, Business School, University of Michigan. 
  7. Damien, P., Wakefield, J. et Walker, S. (1999) Gibbs sampling for Bayesian non-conjugate and hierarchical models by using auxiliary variables. Journal of the Royal Statistical Society (Series B) 61, 331-344. Zbl0913.62028MR1680334
  8. Gelman, A., Gilks, W.R. and Roberts, G.O. (1996) Efficient Metropolis jumping rules. In Bayesian Statistics 5, J.O. Berger, J.M. Bernardo, A.P. Dawid, D.V. Lindley and A.F.M. Smith (Eds.). 599-608. Oxford University Press, Oxford. MR1425429
  9. Geweke, J. (1992) Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments (with discussion. In Bayesian Statistics 4, J.M. Bernardo, J.O. Berger, A.P. Dawid and A.F.M. Smith (Eds.). 169-193. Oxford University Press, Oxford. MR1380276
  10. Gilks, W.R. et Roberts, G.O. (1996) Strategies for improving MCMC. In Markov Chain Monte Carlo in Pratice, W.R. Gilks, S. Richardson and D.J. Spiegelhalter (Eds.), 89-114. Chapman and Hall, London. Zbl0844.62100MR1397966
  11. Hammersley, J.M. et Hancomb, D.C. (1964) Monte Carlo Methods, J. Wiley, New York. Zbl0121.35503
  12. Hastings, W.K. (1970) Monte Carlo sampling methods using Markov chains and their application. Biometrika57, 97-109. Zbl0219.65008
  13. Mengersen, K.L., Robert, C.P. et Guihenneuc-Jouyaux, C. (1999) MCMC convergence diagnostics : a « reviewww» (avec discussion. In Bayesian Statistics 6. J.O. Berger, J.M. Bernardo, A.P. Dawid, D.V. Lindley and A.F.M. Smith (Eds.). Oxford University Press, Oxford, 415- 441. Zbl0957.62019MR1723507
  14. Raftery, A.E. et Lewis, S. (1992) How many iterations in the Gibbs sampler? In Bayesian Statistics 4, J.O. Berger, J.M. Bernardo, A.P. Dawid and A.F.M. Smith (Eds.), 763- 773. Oxford University Press, Oxford. 
  15. Robert, C.P. (1992) L'Analyse Statistique Bayésienne. Economica, Paris. Zbl0827.62006
  16. Robert, C.P. (1996) Méthodes de Monte-Carlo par Chaînes de Markov. Economica, Paris. Zbl0917.60007MR1419096
  17. Smith, A.F.M. et Roberts, G.O. (1993) Bayesian computation via the Gibbs sampler and related Markov chain Monte Carlo methods (avec discussion. Journal of the Royal Statistical Society (Series B) 55, 3-24. Zbl0779.62030MR1210421

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