no. 4
Analyse bayésienne du modèle Logit : algorithme par tranches ou Metropolis-Hastings ?
Revue de Statistique Appliquée, Tome 49 (2001) no. 4, pp. 53-70. 
@article{RSA_2001__49_4_53_0,
     author = {Altaleb, Anas and Robert, Christian P.},
     title = {Analyse bay\'esienne du mod\`ele {Logit} : algorithme par tranches ou {Metropolis-Hastings} ?},
     journal = {Revue de Statistique Appliqu\'ee},
     pages = {53--70},
     publisher = {Soci\'et\'e fran\c{c}aise de statistique},
     volume = {49},
     number = {4},
     year = {2001},
     language = {fr},
     url = {http://www.numdam.org/item/RSA_2001__49_4_53_0/}
}
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
SP  - 53
EP  - 70
VL  - 49
IS  - 4
PB  - Société française de statistique
UR  - http://www.numdam.org/item/RSA_2001__49_4_53_0/
LA  - fr
ID  - RSA_2001__49_4_53_0
ER  - 
%0 Journal Article
%A Altaleb, Anas
%A Robert, Christian P.
%T Analyse bayésienne du modèle Logit : algorithme par tranches ou Metropolis-Hastings ?
%J Revue de Statistique Appliquée
%D 2001
%P 53-70
%V 49
%N 4
%I Société française de statistique
%U http://www.numdam.org/item/RSA_2001__49_4_53_0/
%G fr
%F RSA_2001__49_4_53_0
Altaleb, Anas; Robert, Christian P. Analyse bayésienne du modèle Logit : algorithme par tranches ou Metropolis-Hastings ?. Revue de Statistique Appliquée, Tome 49 (2001) no. 4, pp. 53-70. http://www.numdam.org/item/RSA_2001__49_4_53_0/

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. | MR | Zbl

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.

Brooks S.P. et Roberts, G. (1998) Assessing convergence of Markov chain Monte Carlo algorithms. Statistics and Computing 8, 319-335.

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. | Zbl

Cowles, M.K. et Carlin, B.P. (1996) Markov Chain Monte Carlo convergence diagnostics : a comparative study. Journal of the American Statistical Association 91, 883-904. | MR | Zbl

Damien, P. et Walker, S. (1996) Sampling probability densities via uniform random variables and a Gibbs sampler. Tech. Report, Business School, University of Michigan.

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. | MR | Zbl

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. | MR

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. | MR

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. | MR | Zbl

Hammersley, J.M. et Hancomb, D.C. (1964) Monte Carlo Methods, J. Wiley, New York. | Zbl

Hastings, W.K. (1970) Monte Carlo sampling methods using Markov chains and their application. Biometrika 57, 97-109. | Zbl

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. | MR | Zbl

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.

Robert, C.P. (1992) L'Analyse Statistique Bayésienne. Economica, Paris. | Zbl

Robert, C.P. (1996) Méthodes de Monte-Carlo par Chaînes de Markov. Economica, Paris. | MR | Zbl

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. | MR | Zbl