Christian P. Robert

Selected publications/preprints

[1998|1999|2000|2001|2002|2003|2004|2005|2006|2007|2008|2009|2010]

2010

Beaumont, M.A., Nielsen, R., Robert, C.P., Hey, J., Gaggiotti, O., Knowles, L., Estoup, A., Mahesh, P., Coranders, J., Hickerson, M., Sisson, S., Fagundes, N., Chikhi, L., Beerli, P., Vitalis, R., Cornuet, J.-M., Huelsenbeck, J., Foll, M., Yang, Z., Rousset, F., Balding, D. and Excoffier, L. In defense of model-based inference in phylogeography. Molecular Ecology 19(3), 436-446.
Berger, J.O., Fienberg, S., Raftery. A. and Robert, C.P. Letter on Incoherent Phylogeographic Inference (submitted to PNAS). Early draft available as arXiv:1006.3854
Casella, G. and Robert, C.P. Report of the Editors - 2009. J. Royal Statistical Society Series B, 72(1), 1-2.
Chopin, N., Iacobucci, A., Marin, J.-M., Mengersen, K.L., Robert, C.P., Ryder, R. and Schäfer, C. On particle learning (discussions on Lopes et al.). Bayesian Statistics 9 (to appear). Available as arXiv:1006.0554
Chopin, N. and Robert, C.P. Properties of Nested Sampling. Biometrika (to appear). Available as arXiv:0801.3887
Chopin, N. and Robert, C.P. Discussion on Wilkinson's Parameter inference for stochastic kinetic models of bacterial gene regulation. Available as pdf file
Douc, R. and Robert, C.P, A vanilla Rao--Blackwellisation of Metropolis-Hastings algorithms. Annals of Statistics (to appear). Available as arXiv:0904.2144v2
Hobert, J.O., Roy, V. and Robert, C.P. Improving the Convergence Properties of the Data Augmentation Algorithm with an Application to Bayesian Mixture Modelling. Available as arXiv:0911.4546
Iacobucci, A., Marin, J.-M., and Robert, C.P. On variance stabilisation by double Rao-Blackwellisation. Computational Statistics and Data Analysis 54, 698-710. Available as arXiv:0802.3690
Kilbinger, M., Wraith, D., Robert, C.P. , Benabed, K., Cappé, O., Cardoso, J.-F., Fort, G., Prunet, S., Bouchet, F. Bayesian model comparison in cosmology with population Monte Carlo. Monthly Notices of the Royal Astronomical Society: Letters. 405(4), 2381 - 2390 Available as arXiv:0912.1614.
Marin, J.-M., and Robert, C.P. On resolving the Savage-Dickey paradox. Electronic Journal of Statistics 4, 643-654. Available as arXiv:0910.1452
Robert, C.P. A Search for Certainty: A critical assessment. Bayesian Analysis (with discussion) 05, 02, 213-222. Available as arXiv:1001.5109
Robert, C.P. An attempt at reading Keynes' Treatise on Probability. Available as arxiv:1003.4455
Robert, C.P. Evidence and Evolution: A review. Available as arXiv:1004.5074
Robert, C.P. Computational Statistics: A review. Statistics and Computing (to appear). Available as pdf file
Robert, C.P. Bayesian computational methods. Available as arxiv:1002.2702
Robert, C.P. and Arbel, J. Discussion on Polson and Scott's Sparse Bayesian regularization and prediction. Available as pdf file
Robert, C.P. and Casella, G. Introducing Monte Carlo Methods with R: Solutions to Odd-Numbered Exercises. Available as arXiv:1001.2906
Robert, C.P. and Casella, G. A History of Markov Chain Monte Carlo-Subjective Recollections from Incomplete Data. In Handbook of Markov Chain Monte Carlo: Methods and Applications, edited by Steve Brooks, Andrew Gelman, Galin Jones, and Xiao-Li Meng (to appear). Available as arXiv0808.2902
Robert, C.P. and Casella, G. Generating Random Variables" (version 13). StatProb: The Encyclopedia Sponsored by Statistics and Probability Societies.
Robert, C.P. and Marin. J.-M. On computational tools for Bayesian analysis. In Rethinking Risk Measurement and Reporting. Edited by K. Böcker. Available as arxiv:1002.2684
Robert, C.P., Mengersen, K.L., and Chen, C. Model choice versus model criticism. Letter to PNAS (to appear) (doi:10.1073/pnas.0911260107) Available as arXiv:0909.5673.
Robert, C.P. and Rousseau, J. On Bayesian Analysis. In Rethinking Risk Measurement and Reporting. Edited by K. Böcker. Available as arxiv:1001.4656
Robert, C.P. and Rousseau, J. Discussion on Bernardo's Integrated objective Bayesian estimation and hypothesis testing. Available as pdf file
Rousseau, J. and Robert, C.P. Discussion on Consonni and LaRocca's On moment priors for Bayesian model choice. Available as pdf file

2009

Beaumont, M., Robert, C.P., Marin, J.-M. and Cornuet, J.M. Adaptivity for ABC algorithms: the ABC-PMC scheme. Biometrika 96(4), 983-990. Available as arXiv:08052256
Cornuet, J.M., Marin, J.-M., Mira, A. and Robert, C.P. Adaptive Multiple Importance Sampling, available as arXiv:0907.1254
Cucala, J., Marin, J.-M., Robert, C.P. and Titterington, D.M. A Bayesian reassessment of nearest--neighbour classification. Journal of the American Statistical Association, March 1, 2009, 104(485): 263-273. Available as doi:10.1198/jasa.2009.0125 | arXiv:0802.1357 | pdf file
Grelaud, A., Marin, J.-M., and Robert, C.P, ABC methods for model choice in Gibbs random fields, Notes aux Comptes Rendus de l'Académie des Sciences 347(3-4), 205-210.
Grelaud, A., Marin, J.-M., Robert, C.P., Rodolphe, F. and Tally, F. Likelihood-free methods for model choice in Gibbs random fields. Bayesian Analysis, 3(2), 427-442 . Revised version available as arXiv:0807.2767
Jacob, P., Chopin, N., Robert, C.P., and Rue, H. Comments on "Particle Markov chain Monte Carlo methods" by Andrieu, Doucet and Hollenstein. Journal of the Royal Statistical Society (to appear). Available as arXiv:0911.0985
Lee, K., Mengersen, K.L., Marin, J.-M., and Robert, C.P. Bayesian Inference on Mixtures of Distributions. Perspectives in Mathematical Sciences. Stat. Sci. Interdiscip. Res., 7, 165-202. World Sci. Publ., Hackensack, NJ. Available as arXiv:0804.2413
Marin, J.-M and Robert, C.P., Les bases de la statistique bayésienne, Techniques de l'Ingénieur. AF 605. Earlier version available as pdf file
Robert, C.P Monte Carlo methods in Statistics. Available as arXiv:0909.0389
Robert, C.P On the relevance of the Bayesian approach to Statistics. Review of Economic Analysis (to appear). Available as arXiv:0909.5369
Robert, C.P Discussion of "Natural Induction: An objective Bayes approach" by Berger, Bernardo and Sun, Revista de la Real Academia of Ciencias, Series A Matemáticas) (to appear).
Robert, C.P. and Casella. G. Introducing Monte Carlo Methods with R. Use R! Springer Verlag, New York.
Robert, C.P. and Marin, J.-M. Bayesian Core: The Complete Solution Manual. Available as arXiv:0910.4696
Robert, C.P., Chopin, N. and Rousseau, J. Harold Jeffreys' Theory of Probability revisited (with discussion). Statistical Science 24(2), 141-172 and 191-194 (reply to the discussion). Available as arXiv:0804.3173 and as arXiv:0909.1008 (reply to the discussion).
Robert, C.P. and Wraith, D., Computational methods for Bayesian model choice. AIP Proceedings, Volume 1193, pp. 251-262 Bayesian Inference and maximum entropy methods in Science and Engineering: The 29th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering; doi:10.1063/1.3275622. Available as arXiv:0907.5123.
Wraith, D., Kilbinger, M., Benabed, K., Cappé, O., Cardoso, J.-F., Fort, G., Prunet, S., Robert, C.P. Estimation of cosmological parameters using adaptive importance sampling. Physical Review D, 80, 023502. Available as arXiv:0903.0837

2008

Atchadé, Y., Lartillot, N. and Robert, C.P. Bayesian computation for intractable normalizing constants. Available as arXiv:0804.3152
Ben Mansour, S, Jouini, E., Marin, J.-M., Napp, C. and Robert, C.P. Are risk agents more optimistic? A Bayesian estimation approach. Journal of Applied Econometrics 23(6), 843-860.
Cano, J.A., Salmeron, D. and Robert, C.P. Integral equation solutions as prior distributions for Bayesian model selection. TEST 17(3), 493-504. Available as pdf file
Cappé, O., Douc, R., Gullin, A., Marin, J.-M. and Robert, C.P. Adaptive Importance Sampling in General Mixture Classes. Statistics and Computing 18, 447-459. Available as arXiv:0710.4242v1 | pdf file
Casarin, R. and Robert, C.P. Discussion of "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations” by Rue, Martino, and Chopin. Journal of the Royal Statistical Society pdf file.
Casella, G. and Robert, C.P. Report of the Editors — 2008. Journal of the Royal Statistical Society pdf file.
Chopin, N. and Robert, C.P. Contemplating Evidence: properties, extensions of, and alternatives to Nested Sampling. Programs available as progs.nc.tar.gz and progs.cpr.tar.gz. Revised version available as arXiv:0801.3887
Cornuet, J.M., Santos, F., Beaumont, M.A., Robert, C.P., Marin, J.-M., Balding, D.A., Guillemaud, T. and Estoup, A. Infering population history with DIY ABC: a user-friendly approach to Approximate Bayesian Computation. Bioinformatics 24(23), 2713-2719. Available as arXiv:0804.4372 | pdf file
Marin, J.-M, Casarin, R. and Robert, C.P., Discussion of "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations” by Rue, Martino, and Chopin. Journal of the Royal Statistical Society
Marin, J.-M and Robert, C.P., Approximating the marginal likelihood in mixture models. Bulletin of the Indian Chapter of ISBA V(1), 2-7. Available as arXiv0804.2414 | pdf file
Robert, C.P. Discussion of "Sure independence screening for ultra-high dimensional feature space" by Fan and Lv. Journal of the Royal Statistical Society 70(5), 901. pdf file.
Robert, C.P. Discussion of "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations” by Rue, Martino, and Chopin. Journal of the Royal Statistical Society pdf file.
Robert, C.P. À propos de l'article de N. Vayatis "Bayésiens contre fréquentistes, un faux débat". La Recherche 424, 6.
Robert, C.P. A message from the president. ISBA Bulletin 15(1), 15(2), 15(3), 15(4)
Robert, C.P. Misconceptions on Bayesianism. ISBA Bulletin 15(4), 2-3.
Robert, C.P. and Marin, J.-M., Some difficulties with some posterior probability approximations. Bayesian Analysis 3(2), 427-442. Available as arXiv:0801.3513

2007

Alston, C.L., Mengersen, K.L, Robert, C.P., Thompson, J.M., Littlefield, P.J. and Ball, A.J. Bayesian mixture models in a longitudinal setting for analysing sheep CAT scan images.Computational Statistics and Data Analysis, 51(9), 4282-4296.
Cappé, O. and Robert, C.P. Une approche Monte Carlo adaptative pour l’approximation de lois a posteriori avec application à l’inférence de paramètres cosmologiques. Proceedings, GRETSI, Troyes. Available as pdf file
Chopin, N. and Robert, C.P. Contemplating Evidence: properties, extensions of, and alternatives to Nested Sampling. Available as arXiv:0801.3887 | pdf file
Douc, R., Guillin, A., Marin, J.M., and Robert, C.P., Minimum variance importance sampling via population Monte Carlo. ESAIM Probability and Statistics 11, 427-447. Available as pdf
Douc, R., Guillin, A., Marin, J.-M. and Robert, C.P. Convergence of adaptive mixtures of importance sampling schemes, Annals of Statistics, 35(1), 420-448. Available as pdf|Snw
Kendall, W.S., Marin, J.-M. and Robert, C.P. Confidence bands for Brownian motion and applications to Monte Carlo simulations, Statistics and Computing , 17(1) 1-10. Available as pdf file
Marin, J.-M. and Robert, C.P., Bayesian Core: A Practical Approach to Computational Bayesian Statistics, Springer-Verlag, New York [webpage].
Robert, C.P. The Bayesian Choice. Paperback edition, Springer-Verlag.
Robert, C.P., Discussion of Jain and Neal's ``Splitting and merging components of a nonconjugate Dirichlet process mixture model". Bayesian Analysis. Available as pdf file

2006

Amzal, B., Bois, F.Y., Parent, E. and Robert, C.P. Bayesian optimal design via interacting MCM. J. American Statist. Assoc. 101, 773-785. Available as Postscript file.
Celeux, G., Marin, J.-M., and Robert, C.P., Sélection bayésienne de variables en régression linéaire. Journal de la Société Française de Statistique, 147, 1, 59-79. Available as pdf file
Celeux, G., Marin, J.M. and Robert, C.P. Iterated importance sampling in missing data problems. Computational Statistics and Data Analysis 50(12) 3386-3404. Available as PDF file.
Chopin, N. and Robert, C.P., A discussion of John Skilling's Nested sampling for the Valencia 8 Meeting. Available as pdf file. Reply from the author edited here
Müller, P., Robert, C.P. and Rousseau, J., Sample Size Choice for Microarray Experiments In Bayesian Inference for Gene Expression and Proteomics (eds. K.A. Do, P.Müller and M.Vannucci). Cambridge University Press.
Robert, C.P., Le Choix Bayésien : Principes et implémentation Springer-Verlag, Paris. [Springer order]
Robert, C.P., "A review of Gaussian Markov Random Fields (Theory and Applications) by Håvard Rue and Leonhard Held", Statistics in Medicine (to appear).
Robert, C.P., Three discussions on Bayesian model choice. Cahiers du Ceremade 2006-2. Available as pdf file

2005

Celeux, G., Forbes, F., Robert, C.P. and Titterington, D.M. Deviance information criteria for missing data models Bayesian Analysis (with discussion). Available as PDF file|R program|dataset1|dataset2
Guillin, A., Marin, J.M. and Robert, C.P. Estimation bayesienne approximative par echantillonnage preferentiel. Revue de Statistique Appliquée LIII, 1, 79-95 and Cahiers du Ceremade 0335. Available as PDF file.
Hobert, J.P., Jones, G.L. and Robert, C.P. Using a Markov chain to construct a tractable approximation of an untractable probability distribution. Scandinavian Journal of Statistics et Cahiers du Ceremade 0403. Available as PDF file.
Marin, J.M., Mengersen, K. and Robert, C.P. Bayesian modelling and inference on mixtures of distributions. Handbook of Statistics 25, D. Dey and C.R. Rao (eds). Elsevier-Sciences). Available as PDF file.

2004

Andrieu, C., Doucet, A. and Robert, C.P. Computational Advances for and from Bayesian Analysis. Statistical Science 19(1), 120-129. Available as PDF file.
Cappé, O., Guillin, A., Marin, J.M., and Robert, C.P., Population Monte Carlo. J. Comput. Graph. Stat. 13(4), 907-929 Available as Gzipped postscript.
Casella, G., Robert, C.P. and Wells, M.T., Mixture models, latent variables and partitioned importance sampling. Statist. Method. 1(1), 1-18.
Hobert, J.P. and Robert, C.P. A Mixture Representation of pi with Applications in Markov Chain Monte Carlo and Perfect Sampling. Annals of Applied Proba. 14(3), 1295-1305. Available as Compressed postscript.
Kendall, W.S., Marin, J.M., and Robert, C.P. Brownian confidence bands on Monte Carlo output. Cahiers du Ceremade. Available as PDF file.
Muller, P., Parmigiani, G., Robert, C.P. and Rousseau, J. Optimal Sample Size for Multiple Testing: the Case of Gene Expression Microarrays. J. American Stat. Assoc. 99, 990-1001. [Gzipped postscript|Slides]
Robert, C.P. Discussion on the Inverse Problem half-day. J. Royal Statis. Society. (to appear) [Slides|Written]
Robert, C.P. Bayesian computational methods. Handbook of Computational Statistics (Volume I) Concepts and Fundamentals, Chapter III.11. J. Gentle, W. Härdle, Y. Mori (eds) Springer-Verlag, Heidelberg . Available as PDF file.
Robert, C.P. and Casella, G. Monte Carlo Statistical Methods. Springer-Verlag, New York.

2003

Cappé, O., Robert, C.P., and Rydén, T. Reversible jump MCMC converging to birth-and-death MCMC and more general continuous time samplers. J. Royal Statis. Society Series B 65(3), 679-700. Available as Gzipped postscript.

Dupuis, J.A. and Robert, C.P. Bayesian variable selection in qualitative models by Kullback-Leibler projections. In J. Statistical Planning and Inference 111, 77-94. Available as Postscript.

Hurn, M., Justel, A. and Robert, C.P. Estimating mixtures of regressions. J. Comput. Graph. Stat. 12(1), 1-25. Available as [Compressed postscript | pdf].

Mengersen, K.L. and Robert, C.P. The pinball sampler. Bayesian Statistics 7 (edited by J.M. Bernardo, A.P. Dawid, J.O. Berger, and M. West) [Compressed postscript]

Philippe, A. and Robert, C.P. Perfect simulation of positive Gaussian distributions. Statistics and Computing 13(2), 179-186. [Compressed postscript]

Robert, C.P. Discussion of Kong, McCullagh, Nicolae, Tan, and Meng. J. Royal Statis. Society. 65(3), 606-609. [Slides |Written ]

Robert, C.P. Discussion of Brooks, Giudici and Roberts, J. Royal Statis. Society. 65(1), 39-42 Gzipped postscript.

Robert, C.P. and Rousseau, J. A mixture approach to Bayesian goodness of fit (revised version). Available as PDF file.

Mount Temple, Canadian Rockies, Aug. 2003

2002

Casella, G., Mengersen, K.L., Robert, C.P., and Titterington, D.M. Perfect Slice Samplers for Mixtures of Distributions. J. Royal Statis. Society Series B 64(4), 777-790. Available as Compressed postscript.
DeIorio, M. and Robert, C.P., Discussion of Spiegelhalter et al., J. Royal Statis. Society Series B 64(4), 629-630. Available as Gzipped postscript.
Douc, R., O. Cappé, E. Moulines, and C. P. Robert. On the Convergence of the Monte Carlo Maximum Likelihood Method for Latent Variable Models. Scandinavian J. Statist. 29(4), 615-636. [Abstract][Compressed postscript]
Doucet, A., Godsill, J.A. and Robert, C.P. Marginal maximum a posteriori estimation using Markov chain Monte Carlo. Statistics and Computing 12, 77-84 [Compressed postscript]
Marin, J.-M. and Robert, C.P. (2002) Discussion on a paper of S. L. Lauritzen and T. S. Richardson: Chain graph models and their causal interpretation,
J. Royal Statis. Society Series B, 64, 3
Robert, C.P. A review of Finite Mixture Models by G. McLachlan and D. Peel. J. American Statist. Assoc. (It actually never appeared!).
Robert, C.P. and Rousseau, J. A Mixture Approach to Bayesian Goodness of Fit. Cahier du CEREMADE 02009. Available as Gzipped postscript.
Robert, C.P. and Titterington, D.M. Discussion of Spiegelhalter et al., J. Royal Statis. Society Series B 64(4), 621-622. Available as Gzipped postscript.

2001

Altaleb, A. and Robert, C.P. Analyse bayesienne du modele Logit : algorithme par tranches ou Metropolis-Hastings ? Revue de Statistique Appliquée 49, 53-70.
Andrieu, Ch., and Robert, C.P. Controlled MCMC for Optimal Sampling. Available as Gzipped postscript.
Casella, G., Lavine, M. and Robert, C.P. Explaining the Perfect Sampler. The American Statistician 55(4), 299-305. Available as Compressed pdf file.
Philippe, A. and Robert, C.P. Riemann sums for MCMC estimation and convergence monitoring. Statistics and Computing 11, 103-115.
Robert, C.P. The Bayesian Choice. second edition, Springer-Verlag.

2000

Cappé, O. and Robert, C.P. Ten years and still running! J. American Statist. Assoc. 95 (4), 1282-1286. Available as html file.
Casella, G., Robert, C.P. and Wells, M.T. Rao-Blackwellization of Generalized Accept-Reject Schemes. Tech. Report, Dept. of Statistics, UFL. Available as Compressed postscript.
Casella, G., Robert, C.P. and Wells, M.T. Mixture models, latent variables and partitioned importance sampling. Tech. Report DT-2000-03, CREST, INSEE, Paris. Available as Compressed postscript.
Celeux, G., Hurn, M. and Robert, C.P. Computational and inferential difficulties with mixture posterior distributions. J. American Statist. Assoc. 95 957-970.
Doucet, A. and Robert, C.P. Maximum a posteriori parameter estimation for hidden Markov models. Tech. Report, Signal Processing Group, University of Cambridge. Available as Compressed postscript.
Fourdrinier, D., Philippe, A. and Robert, C.P. Estimation of a non-centrality parameter under Stein type like losses J. Statistical Planning and Inference 87(1), 43-54.
Robert, C.P., Rydén, T. and Titterington, D.M. Bayesian inference in hidden Markov models through jump Markov chain Monte Carlo J. Royal Statis. Society Series B 62(1), 57-75.

1999

Billio, M., Monfort, A. Robert, C.P. Bayesian estimation of switching ARMA models. J. Econometrics, 93 229-255. [Abstract][Full paper] (PDF).
Gruet, M.A., Philippe, A. and Robert, C.P. MCMC Control Spreadsheets for Exponential Mixture Estimation. J. Comput. Graph. Stat. 8, 298-317. See also the related software expmix.
Hobert, J. and Robert, C.P. Eaton's Markov chain, its conjugate partner and P-admissibility. Annals of Statistics 27, 361-373.
Hobert, J., Robert, C.P. and Titterington, D.M. On perfect simulation for some mixtures of distributions. Statistics and Computing 9 287-298.
Mengersen, K. L., Robert, C.P. and Guihenneuc-Jouyaux, C. MCMC convergence diagnostics: a "reviewww". In Bayesian Statistics 6 (J. Berger, J. Bernardo, A.P. Dawid and A.F.M. Smith, eds.), 415-440. Oxford Sciences Publications.
Robert, C.P. and Mengersen, K. L. Reparameterisation Issues in Mixture Modelling and their Bearing on the Gibbs Sampler. Computational Statistics and Data Analysis 29, 325-343. [Abstract][Full text] (PDF).
Robert, C.P., RydÃ©n, T. and Titterington, D.M. Convergence Controls for MCMC Algorithms with Applications to Hidden Markov Chains.J. Statist. Comput. Simulation 64, 327-355.

1998

Billio, M., Monfort, A. Robert, C.P. The simulated likelihood method. Tech. report DT9821, CREST, INSEE, Paris. Available as Compressed postscript.
Casella, G. and Robert, C.P. Post-Processing Accept-Reject Samples: Recycling and Rescaling. J. Comput. Graph. Stat. 7(2), 139-157 (Abstract) (See the review 98b:62026 in the Mathematical Reviews.)
Goutis, C. and Robert, C.P. Model Choice in generalized linear models: a Bayesian approach via Kullback-Leibler projections.Biometrika 85, 29-37. (Abstract)
Guihenneuc-Jouyaux, C., Knight, S., Mengersen, K.L., Richardson, S. and Robert, C.P. MCMC convergence diagnostics in action. Tech. report, CREST, INSEE, Paris. Available as Compressed postscript.
Guihenneuc-Jouyaux, C. and Robert, C.P. Discretizations of Continuous State Space Markov Chains for MCMC Convergence Assessment. J. American Statist. Assoc. 93, 1055-1067.
Robert, C.P. A pathological MCMC algorithm and its use as a benchmark for convergence assessment techniques. Comput. Stat. 13, 169-184.
Robert, C.P. and Titterington, D.M. Reparameterisation strategies for hidden Markov models and Bayesian approaches to maximum likelihood estimation. Statistics and Computing 8(2), 145-158.

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