• Published

1. Theoretical papers:
           

• McVinish, R. Mengersen, K., Rousseau J., Nur, D. and Guihenneuc C. (2007) : Recentered importance sampling with applications to Bayesian model validation. JCGS. pdf

• V. Rivoirard and J. Rousseau (2011) Posterior concentration rates for infinite dimensional exponential families. Bayesian Analysis pdf

• J. Rousseau, N. Chopin and B. Liseo (2011) Bayesian nonparametric estimation of the spectral density of a long or intermediate memory Gaussian process Annals of Statist. pdf

• J. Rousseau and K. Mengersen (2011)  Asymptotic behaviour of the posterior distribution in overfitted models. JRSSB. pdf

• Lieberman, O., Rosemarin, R. and Rousseau, J. (2010) : Asymptotic Theory for Maximum Likelihood Estimation of the Memory Parameter in Stationary Gaussian Processess.  Econometric Theory pdf

• W. Kruijer, J. Rousseau and A. van der Vaart (2010) Adaptive Bayesian Density Estimation with Location-Scale Mixtures . Electronic Journal of Statistics pdf


• J. Rousseau (2009) : Rates of convergence for the posterior distributions of mixtures of betas and adaptive nonparamatric estimation of the density. Annals of Statistics, pdf


• C.P. Robert, N. Chopin and J. Rousseau (2009) : Harold Jeffreys' theory of probability revisited.  Statistical Science


• R.McVinish, J. Rousseau and K. Mengerson (2008): Bayesian Goodness-of-Fit Testing with Mixtures of Triangular Distributions. Scandinavian journal of statistics pdf


• D. Fraser and J. Rousseau (2008) : Studentization and the determination of p-values. Biometrika 95, 1-16. pdf


• A. Chambaz and J. Rousseau (2008): Bounds for Bayesian order identification with application to mixtures. Annals of Statistics, 36, 938-962  pdf


• J. Rousseau (2007): Approximating Interval hypothesis : p-values and Bayes factors. Bayesian Statistics 8 (J. M. Bernardo, J. O. Berger, A. P. Dawid and A. F. M. Smith, eds.) Oxford: University Press. pdf


• G. Gayraud and J. Rousseau (2005): Rates of convergence for a Bayesian level set estimation. Scand. Journ. Statist. 14, 1, 75-94. ps


• G. Gayraud and J. Rousseau (2005): Consistency results on nonparametric Bayesian estimation of level sets using spatial priors. test  pdf


• C. Guihenneuc et J. Rousseau (2005): Laplace expansions in MCMC algorithms for latent variable models. Journal of Computational and Graphical Statistics. 32 (4), 639-660.


• O. Lieberman, J. Rousseau, D. Zucker (2003): Valid asymptotic expansions for the maximum likelihood estimator of the parameter of a stationary, Gaussian, strongly dependent process, Annals of Statistics, 31, 586-612.


• A. Philippe, J. Rousseau (2003) : Non-informative priors for Gaussian long-memory processes, Bernoulli,  8, 451-473.


• D. Zucker, J. Rousseau, A. Philippe et O. Lieberman (2003) : Asymptotic expansions for long-memory stationary Gaussian processes. In Foundations of Statistical Inference, Y.Haitovsky, H.R. Lerche, Y. Ritov (eds.). Physica-Verlag, Heidelberg.


• J. Rousseau (2002) : Coverage properties of HPD regions in the discrete case, Journal of Multivariate Analysis, 83,1-21.


• M. Ghosh, J. Rousseau, D. Kim (2001) : Non-informative priors for the bivariate Fieller-Creasy problem, Statistics and Decisions, 19, No. 3, 227.


• O. Lieberman, J. Rousseau, D. Zucker (2001) : Small sample asymptotics for the sample autocorrelation function under long-range dependence, Econometric theory, 17, No.1, 257-275.


• O. Lieberman, J. Rousseau et D. Zucker (2000) : Small sample Likelihood-based inference in the ARFIMA model, Econometric theory, 16, No. 2, 231-248 .


• J. Rousseau (2000) : Coverage properties of one-sided intervals in the discrete case and applications to matching priors, Annals of the Institute of statistical mathematics, 52, no 1, 28-42.


• J. Rousseau (1997) : Asymptotic Bayes risk for a general class of losses, Statistics and Probability Letters, 35, 115-121.

2. Methodological Papers.

• D. Gadja, C. Guihenneuc, J. Rousseau, K. Mengersen and D. Nur (2010): Use in practice of importance sampling for repeated MCMC for Poisson models.  Elect. Journ. Statist.


• P. Muller, C. Robert and J. Rousseau (2006) : Sample Size Choice for Microarray Experiments In Bayesian Inference for Gene Expression and Proteomics. (eds. K.-A. Do, P.Muller and M.Vannucci). Cambridge University Press.

• P. Muller, G. Parimigiani, C. Robert et J. Rousseau (2004): Optimal sample sizes for multiple testing: the case of gene expression microarrays. J.A.S.A., T. & M, 99, 990-1001.

 3. Applied papers

• D. Nur, D. Allingham, J. Rousseau, K. Mengersen and R. McVinish (2008 : Bayesian analysis of DNA sequence segmentation: A prior sensitivity analysis . Comp. Statist. Data Anal.
  
• S.L. Choy, K. Mengersen, J. Rousseau (2008): Encoding Expert Opinion on Skewed Non-Negative Distributions. Journ.  Appl. Probab. Statist. 3
• I. Albert, E. Grenier, J.B. Denis et J. Rousseau (2006) : Quantitative Risk Assessement from Farm to Fork and Beyond: a global Bayesian approach concerning food-borne diseases.  Risk Analysis. 28:2, 558-571.
• Nur Darfiana, Allingham David, Rousseau J, Mengersen K L and McVinish (2007): Bayesian analysis of DNA sequence segmentation: A prior sensitivity analysis . Comp. Statist. Data Anal. pdf

4.  Discussions

• J. Rousseau (2004): Discussion sur : Bayesian inference for Elliptical linear models: Conjugate analysis and model comparison by C.R.B. Arellano-Valle, P. Iglesias, I. Vidal, Bayesian Statistics 7, eds J. M. Bernardo et {\it al.}, Amsterdam: North Holland.
• C. Robert et J. Rousseau (2004) : Discussion sur : Bayesian and Frequentist Multiple Testing, de C. Genovese et L. Wasserman. Bayesian Statistics 7, eds J. M. Bernardo et al.,Amsterdam: North Holland.

5. Book chapters

• Robert, C.P. and Rousseau, J.(2009): On Bayesian Data Analysis .  In "Bayesian Methods and Expert Elicitation", Risk Book, London
• Robert, C.P, Marin, J.M. and Rousseau, J. (2010)  Bayesian inference. In  Handbook of Statistical Systems Biology

• Preprint
  

• J. Rousseau and T. Choi (2011) Bayes factor consistency in regression problems. pdf
  
• S. Khazaei, J. Rousseau and F. Balabdaoui (2010) Nonparametric Bayesian estimation of densities under monotonicity constraint pdf
• J.M. Marin, N. Pillai, C.P. Robert and J. Rousseau (2011) Evaluating statistic appropriateness for Bayesian model choice. pdf
• J. Rousseau and W. Kruijer (2011) Adaptive Bayesian Estimation of a spectral density. pdf
• I. Albert, S. Donnet, C. Guihenneuc-Jouyaux, S. Low-Choi, K. Mengersen and J. Rousseau (2010) Combining expert opinions in prior elicitation. pdf
  
• V. Rivoirard and J. Rousseau (2009) Bernstein-von Mises Theorem for linear functionals of the density  pdf
• Wraith D, Mengersen K, Rousseau J. and Hussein T. (2009) A Bayesian hierarchical mixture model for aerosol particle size distributions
• C. Robert et J. Rousseau (2003): Bayesian Goodness of Fit -A Mixture Approach to Bayesian Goodness of Fit.
• J. Rousseau and I. Skovgaard (2003): On the error rate for asymptotic chi-squared distributions in the lattice case.
• J. Rousseau (1997): Asymptotic coverages of joint two-sided intervals.
• J. Rousseau (1997) : Expansions of penalized likelihood ratio statistics and consequences on Matching priors for HPD regions. Document de travail, CREST, n° 9601.