CEREMADE
Rousseau Judith
Full Professor
Publications
Articles
Moss D., Rousseau J. (2024), Efficient Bayesian estimation and use of cut posterior in semiparametric hidden Markov models, Electronic Journal of Statistics, vol. 18, n°1, p. 1815-1886 
Sulem D., Rivoirard V., Rousseau J. (2024), Bayesian estimation of nonlinear Hawkes processes, Bernoulli, vol. 30, n°2, p. 1257–1286
Naulet Z., Rousseau J., Caron F. (2024), Asymptotic Analysis of Statistical Estimators related to MultiGraphex Processes under Misspecification, Bernoulli, vol. 30, n°4, p. 2644-2675
Rockova V., Rousseau J. (2023), Ideal Bayesian Spatial Adaptation, Journal of the American Statistical Association
Robert C., Rousseau J. (2023), A special issue on Bayesian Inference: Challenges, Perspective, and Prospects, Philosophical Transactions. Physical, Mathematical and Engineering Sciences, vol. 381, n°2247
Caron F., Panero F., Rousseau J. (2023), On sparsity, power-law, and clustering properties of graphex processes, Advances in Applied Probability, vol. 55, n°4, p. 1211-1253
Browning R., Sulem D., Mengersen K., Rivoirard V., Rousseau J. (2021), Simple discrete-time self-exciting models can describe complex dynamic processes: A case study of COVID-19, PLoS ONE, vol. 16, n°4
Donnet S., Rivoirard V., Rousseau J. (2020), Nonparametric Bayesian estimation for multivariate Hawkes processes, Annals of Statistics, vol. 48, n°5, p. 2698-2727
Frazier D., Robert C., Rousseau J. (2020), Model Misspecification in ABC: Consequences and Diagnostics, Journal of the Royal Statistical Society. Series B, Statistical Methodology, vol. 82, n°2, p. 421-444
Frazier D., Martin G., Robert C., Rousseau J. (2018), Asymptotic Properties of Approximate Bayesian Computation, Biometrika, vol. 105, n°3, p. 593-607
Gassiat E., Rousseau J., Vernet E. (2018), Efficient semiparametric estimation and model selection for multidimensional mixtures, Electronic Journal of Statistics, vol. 12, n°1, p. 703-740
Donnet S., Rivoirard V., Rousseau J., Scricciolo C. (2018), Posterior concentration rates for empirical Bayes procedures, with applications to Dirichlet Process mixtures, Bernoulli, vol. 24, n°1, p. 231-256
Donnet S., Rivoirard V., Rousseau J., Scricciolo C. (2017), Posterior concentration rates for counting processes with Aalen multiplicative intensities, Bayesian Analysis, vol. 12, n°1, p. 53-87
Robert C., Rousseau J. (2017), How Principled and Practical Are Penalised Complexity Priors?, Statistical Science, vol. 32, n°1, p. 36-40
Naulet Z., Rousseau J. (2017), Posterior concentration rates for mixtures of normals in random design regression, Electronic Journal of Statistics, vol. 11, n°2, p. 4065-4102
Gassiat E., Rousseau J. (2016), Nonparametric finite translation hidden Markov models and extensions, Bernoulli, vol. 22, n°1, p. 193-212
Robert C., Rousseau J. (2016), Nonparametric Bayesian Clay for Robust Decision Bricks, Statistical Science, vol. 31, n°4, p. 506-510
Arbel J., Mengersen K., Rousseau J. (2016), Bayesian nonparametric dependent model for partially replicated data: The influence of fuel spills on species diversity, Annals of Applied Statistics, vol. 10, n°3, p. 1496-1516
Rousseau J. (2016), On the Frequentist Properties of Bayesian Nonparametric Methods, Annual Reviews of Statistics and its applications, vol. 3:211-231, p. 24
Donnet S., Rousseau J. (2016), Bayesian Inference for Partially Observed Multiplicative Intensity Processes, Bayesian Analysis, vol. 11, n°1, p. 151-190
Hoffmann M., Rousseau J., Schmidt-Hieber J. (2015), On adaptive posterior concentration rates, Annals of Statistics, vol. 43, n°5, p. 2259-2295
Taeryon C., Rousseau J. (2015), A note on Bayes factor consistency in partial linear models, Journal of Statistical Planning and Inference, vol. 166, p. 158-170
van Havre Z., White N., Rousseau J., Mengersen K. (2015), Overfitting Bayesian Mixture Models with an Unknown Number of Components., PLoS ONE, vol. 10, n°7, p. e0131739
Castillo I., Rousseau J. (2015), A Bernstein-von Mises theorem for smooth functionals in semiparametric models, Annals of Statistics, vol. 43, n°6, p. 2353-2383
Petrone S., Scricciolo C., Rousseau J., Rizzelli S. (2014), Empirical Bayes methods in classical and Bayesian inference, Metron, vol. 72, n°2, p. 201-215
Rousseau J., Petrone S., Scricciolo C. (2014), Bayes and empirical Bayes : Do they merge?, Biometrika, vol. 101, n°2, p. 285-302
Hussein T., Alston C., Mengersen K., Rousseau J., Wraith D. (2014), Using informative priors in the estimation of mixtures over time with application to aerosol particle size distributions, Annals of Applied Statistics, vol. 8, n°1, p. 232-258
Rousseau J., Pillai N., Marin J-M., Robert C. (2014), Relevant statistics for Bayesian model choice, Journal of the Royal Statistical Society. Series B, Statistical Methodology, vol. 76, n°5, p. 833-859
Rousseau J., Gassiat E. (2014), About the posterior distribution in hidden Markov models with unknown number of states, Bernoulli, vol. 20, n°4, p. 2039-2075
Arbel J., Gayraud G., Rousseau J. (2013), Bayesian Optimal Adaptive Estimation Using a Sieve Prior, Scandinavian Journal of Statistics, vol. 40, n°3, p. 549-570
Robert C., Rousseau J., Gelman A. (2013), Inherent difficulties of non-Bayesian likelihood-based inference, as revealed by an examination of a recent book by Aitkin, Statistics & Risk Modeling, vol. 30, n°2, p. 105-120
Rousseau J., Chopin N., Liseo B. (2013), Computational aspects of Bayesian spectral density estimation, Journal of Computational and Graphical Statistics, vol. 22, n°3, p. 533-557
Kruijer W., Rousseau J. (2013), Bayesian semi-parametric estimation of the long-memory parameter under FEXP-priors, Electronic Journal of Statistics, vol. 7, p. 2947-2969
Rousseau J., Rivoirard V. (2012), Bernstein–von Mises theorem for linear functionals of the density, Annals of Statistics, vol. 40, n°3, p. 1489-1523
Mengersen K., Guihenneuc-Jouyaux C., Low-Choy S., Rousseau J., Albert I., Donnet S. (2012), Combining Expert Opinions in Prior Elicitation, Bayesian Analysis, vol. 7, n°3, p. 503-532
Rousseau J., Chopin N., Liseo B. (2012), Bayesian nonparametric estimation of the spectral density of a long or intermediate memory Gaussian process, Annals of Statistics, vol. 40, n°2, p. 964-995
Lieberman O., Rosemarin R., Rousseau J. (2012), Asymptotic Theory for Maximum Likelihood Estimation of the Memory Parameter in Stationary Gaussian Processes, Econometric Theory, vol. 28, n°2, p. 457-470
Rivoirard V., Rousseau J. (2012), Posterior concentration rates for infinite dimensional exponential families, Bayesian Analysis, vol. 7, n°2, p. 311-334
Rousseau J., Mengersen K. (2011), Asymptotic behaviour of the posterior distribution in overfitted mixture models, Journal of the Royal Statistical Society. Series B, Statistical Methodology, vol. 73, n°5, p. 689-710
Rousseau J. (2010), Rates of convergence for the posterior distributions of mixtures of Betas and adaptive nonparametric estimation of the density, Annals of Statistics, vol. 38, n°1, p. 146-180
Mengersen K., Rousseau J., Mcvinish R. (2009), Bayesian Goodness-of-Fit Testing with Mixtures of Triangular Distributions, Scandinavian Journal of Statistics, vol. 36, p. 337-354
Rousseau J., Deman P., Guerquin-Kern J-L., Di Wu T., Elleaume H., Gouget B. (2009), Intracerebral delivery of 5-iodo-2'-deoxyuridine in combination with synchrotron stereotactic radiation for the therapy of the F98 glioma., Journal of Synchrotron Radiation, vol. 16, n°Pt 4, p. 573-581
Robert C., Chopin N., Rousseau J. (2009), Rejoinder: Harold Jeffreys' Theory of Probability Revisited, Statistical Science, vol. 24, n°2, p. 191-194
Robert C., Rousseau J., Chopin N. (2009), Harold Jeffreys' Theory of Probability revisited, Statistical Science, vol. 24, n°2, p. 141-172
Mcvinish R., Allingham D., Rousseau J., Nur D., Mengersen K. (2009), Bayesian hidden Markov Model for DNA segmentation : A prior sensitivity analysis, Computational Statistics & Data Analysis, vol. 53, n°5, p. 1873-1882
Grenier E., Rousseau J., Denis J-B., Albert I. (2008), Quantitative Risk Assessment from Farm to Fork and Beyond: A Global Bayesian Approach Concerning Food-Borne Diseases, Risk Analysis, vol. 28, n°2, p. 557-571
Chambaz A., Rousseau J. (2008), Bounds for Bayesian order identification with application to mixtures, Annals of Statistics, vol. 36, n°2, p. 938-962
Low-Choy S., Mengersen K., Rousseau J. (2008), Encoding expert opinion on skewed non-negative distributions, Journal of Applied Probability and Statistics , vol. 3, n°1, p. 1-21
Rousseau J., Fraser D. (2008), Studentization and deriving accurate p-values, Biometrika, vol. 95, n°1, p. 1-16
Gayraud G., Rousseau J. (2007), Consistency results on nonparametric Bayesian estimation of level sets using spatial priors, Test, vol. 16, n°1, p. 90-108
Gayraud G., Rousseau J. (2005), Rates of Convergence for a Bayesian Level Set Estimation, Scandinavian Journal of Statistics, vol. 32, n°4, p. 639-660
Rousseau J., Parmigiani G., Robert C., Müller P. (2004), Optimal Sample Size for Multiple Testing: The Case of Gene Expression Microarrays, Journal of the American Statistical Association, vol. 99, n°468, p. 990-1001
Chapitres d'ouvrage
Mengersen K., Johnson H., White N., Silburn P., Rousseau J. (2012), Hidden Markov models for complex stochastic processes: A case study in electrophysiology., in Pettitt, Anthony N., Case Studies in Bayesian Statistical Modelling and Analysis Wiley, p. 598
Marin J-M., Robert C., Rousseau J. (2011), Bayesian Inference and Computation, in Stumpf, Michael, Handbook of Statistical Systems Biology Wiley, p. 600
Robert C., Rousseau J. (2010), On Bayesian Data Analysis, in Böcker, Klaus, Rethinking Risk Measurement and Reporting, London: Infopro Digital Risk Ltd, p. 527
Communications avec actes
Rousseau J., Salomond J-B., Scricciolo C. (2014), On some aspects of the asymptotic properties of Bayesian approaches in nonparametric and semiparametric models, in , ESAIM - Journée MAS 2012, Clermont-Ferrand, ESAIM: Proceedings and Surveys, 159-171 p.
Rousseau J. (2007), Approximating Interval hypothesis : p-values and Bayes factors, in West, M., Valencia International Meeting on Bayesian Statistics 2006, Oxford, Oxford University Press, 688 p.
Communications sans actes
Rosa P., Borovitskiy V., Terenin A., Rousseau J. (2023), Posterior Contraction Rates for Matérn Gaussian Processes on Riemannian Manifolds, NeurIPS 2023, La Nouvelle-Orléans, États-Unis
Arbel J., Mengersen K., Rousseau J. (2014), On diversity under a Bayesian nonparametric dependent model, SIS 2014, Cagliari, Italie
Rousseau J. (2014), On consistency issues in Bayesian nonparametric testing - a review, SIS 2014, Cagliari, Italie
Donnet S., Rousseau J., Rivoirard V. (2014), Non parametric Bayesian estimation for Hawkes processes, International Society for Bayesian Analysis World Meeting, ISBA 2014, Cancun, Mexique
Donnet S., Rousseau J., Rivoirard V., Scricciolo C. (2014), On Convergence Rates of Empirical Bayes Procedures, SIS 2014, Cagliari, Italie
Rousseau J., Mengersen K., Low-Choy S., Murray J. (2010), How Should We Combine Expert Opinions: On Elicitation, Encoding, Priors or Posteriors?, 9th Valencia International Meeting on Bayesian Statistics - 2010 World Meeting of the International Society for Bayesian Analysis, Benidorm, Espagne
Khazaei S., Rousseau J. (2010), Bayesian Nonparametric Inference of Decreasing Densities, 42èmes Journées de Statistique, Marseille, France
Mengersen K., Rousseau J. (2010), Asymptotic Behaviour of the Posterior Distribution in Mixture Models with too many Components, 9th Valencia International Meeting on Bayesian Statistics - 2010 World Meeting of the International Society for Bayesian Analysis, Benidorm, Espagne
Kruijer W., Rousseau J. (2010), On Bayesian Estimation of the Long-Memory Parameter in the FEXP-Model for Gaussian Time Series, 9th Valencia International Meeting on Bayesian Statistics - 2010 World Meeting of the International Society for Bayesian Analysis, Benidorm, Espagne
Rousseau J. (2009), Rates of convergence for the posterior distributions of mixtures of betas and adaptive nonparamatric estimation of the density, 7th Workshop on Bayesian Nonparametrics, Moncalieri, Italie
Rousseau J., Van Der Vaart A., Kruijer W. (2009), Adaptive Bayesian Density Estimation with Location-Scale Mixtures, 7th Workshop on Bayesian Nonparametrics, Moncalieri, Italie
Albert I., Grenier E., Denis J-B., Rousseau J. (2007), A global Bayesian approach for quantitative risk assessment (QRA) from farm to illness - application to campylobacteriosis through broiler, 5th International Conference of Predictive Modelling in Food, Athenes, Grèce
Prépublications / Cahiers de recherche
Naulet Z., Rousseau J., Caron F. (2022), Asymptotic Analysis of Statistical Estimators related to MultiGraphex Processes under Misspecification, Paris, Cahier de recherche CEREMADE, Université Paris Dauphine-PSL, 79 p.
Hairault A., Robert C., Rousseau J. (2022), Evidence estimation in finite and infinite mixture models and applications, Paris, Cahier de recherche CEREMADE, Université Paris Dauphine-PSL, 43 p.
Kamary K., Mengersen K., Robert C., Rousseau J. (2017), Testing hypotheses via a mixture estimation model, Paris, Cahier de recherche CEREMADE, Université Paris Dauphine-PSL, 37 p.
Robert C., Rousseau J. (2016), Some comments about A Bayesian criterion for singular models by M. Drton and M. Plummer, Paris, Cahier de recherche CEREMADE, Université Paris Dauphine-PSL, 4 p.
Rousseau J., Alquier P., Chopin N., Cottet V. (2014), Bayesian matrix completion: prior specification and consistency, Paris, Université Paris-Dauphine, 26 p.
Donnet S., Rivoirard V., Rousseau J., Scricciolo C. (2014), Posterior concentration rates for empirical Bayes procedures, with applications to Dirichlet Process mixtures. Supplementary material, Paris, Université Paris-Dauphine, 4 p.
Rousseau J., Gassiat E. (2013), Non parametric finite translation mixtures with dependent regime, Paris, Université Paris-Dauphine, 26 p.
Taeryon C., Rousseau J. (2012), Bayes factor consistency in regression problems, Paris, Université Paris-Dauphine, 22 p.
Robert C., Marin J-M., Pillai N., Rousseau J. (2011), Evaluating statistic appropriateness for Bayesian model choice, Paris, Université Paris-Dauphine, 18 p.
Kruijer W., Rousseau J. (2011), Adaptive Bayesian Estimation of a spectral density, Paris, Université Paris-Dauphine, 14 p.
Liseo B., Rousseau J. (2006), Bayesian nonparametric estimation of the spectral density of a long memory Gaussian time series, Paris, Cahiers du CEREMADE, 51 p.
Fraser D., Rousseau J. (2005), Developing p-values: a Bayesian-frequentist convergence, Paris, Cahiers du CEREMADE, 16 p.
McVinish R., Mengersen K., Rousseau J. (2005), Bayesian Mixtures of Triangular distributions with application to Goodness-of-Fit Testing, Paris, Cahiers du CEREMADE, 45 p.
Robert C., Rousseau J. (2002), A Mixture Approach to Bayesian Goodness of Fit, Paris, Université Paris-Dauphine, 25 p.