Judith Rousseau

Judith Rousseau

Bayesian statistics, Asymptotics, Nonparametric statistics

I work on Bayesian statistics, trying to understand the connexions between Bayesian and frequentist methods in particular in complex or large dimensional models.

Publications

2018

  • D. T. Frazier, G. M. Martin, C. P. Robert, J. Rousseau, Asymptotic properties of approximate Bayesian computation, arXiv preprint arXiv:1607.06903, 2018.
  • S. Donnet, V. Rivoirard, J. Rousseau, C. Scricciolo, . others, Posterior concentration rates for empirical Bayes procedures with applications to Dirichlet process mixtures, Bernoulli, vol. 24, no. 1, 231–256, 2018.

2017

  • F. Caron, J. Rousseau, On sparsity and power-law properties of graphs based on exchangeable point processes, arXiv preprint arXiv:1708.03120, 2017.
  • S. Donnet, V. Rivoirard, J. Rousseau, C. Scricciolo, . others, Posterior concentration rates for counting processes with Aalen multiplicative intensities, Bayesian Analysis, vol. 12, no. 1, 53–87, 2017.
  • N. Bochkina, J. Rousseau, . others, Adaptive density estimation based on a mixture of Gammas, Electronic Journal of Statistics, vol. 11, no. 1, 916–962, 2017.
  • J. Rousseau, B. Szabo, Asymptotic behaviour of the empirical Bayes posteriors associated to maximum marginal likelihood estimator, Ann. Statist., vol. 45, no. 2, 833–865, Apr. 2017.

2016

  • J. Rousseau, On the frequentist properties of bayesian nonparametric methods, Annual Review of Statistics and Its Application, vol. 3, 211–231, 2016.
  • J. Arbel, K. Mengersen, J. Rousseau, . others, Bayesian nonparametric dependent model for partially replicated data: the influence of fuel spills on species diversity, The Annals of Applied Statistics, vol. 10, no. 3, 1496–1516, 2016.
  • E. Gassiat, J. Rousseau, . others, Nonparametric finite translation hidden Markov models and extensions, Bernoulli, vol. 22, no. 1, 193–212, 2016.

2015

  • Z. Havre, N. White, J. Rousseau, K. Mengersen, Overfitting Bayesian mixture models with an unknown number of components, PloS one, vol. 10, no. 7, e0131739, 2015.
  • I. Castillo, J. Rousseau, A Bernstein-von Mises theorem for smooth functionals in semiparametric models, Ann. Statist., vol. 43, no. 6, 2353–2383, Dec. 2015.
  • M. Hoffmann, J. Rousseau, J. Schmidt-Hieber, On adaptive posterior concentration rates, Ann. Statist., vol. 43, no. 5, 2259–2295, Oct. 2015.

2014

  • D. Wraith, K. Mengersen, C. Alston, J. Rousseau, T. Hussein, . others, Using informative priors in the estimation of mixtures over time with application to aerosol particle size distributions, The Annals of Applied Statistics, vol. 8, no. 1, 232–258, 2014.
  • E. Gassiat, J. Rousseau, . others, About the posterior distribution in hidden Markov models with unknown number of states, Bernoulli, vol. 20, no. 4, 2039–2075, 2014.
  • P. Alquier, V. Cottet, N. Chopin, J. Rousseau, Bayesian matrix completion: prior specification, arXiv preprint arXiv:1406.1440, 2014.
  • S. Petrone, S. Rizzelli, J. Rousseau, C. Scricciolo, Empirical Bayes methods in classical and Bayesian inference, Metron, vol. 72, no. 2, 201–215, 2014.
  • S. Petrone, J. Rousseau, C. Scricciolo, Bayes and empirical Bayes: do they merge?, Biometrika, vol. 101, no. 2, 285–302, 2014.
  • J. Marin, N. S. Pillai, C. P. Robert, J. Rousseau, Relevant statistics for Bayesian model choice, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol. 76, no. 5, 833–859, 2014.

2013

  • J. Arbel, G. Gayraud, J. Rousseau, Bayesian optimal adaptive estimation using a sieve prior, Scandinavian journal of statistics, vol. 40, no. 3, 549–570, 2013.
  • R. McVinish, K. Mengersen, D. Nur, J. Rousseau, C. Guihenneuc-Jouyaux, Recentered importance sampling with applications to Bayesian model validation, Journal of Computational and Graphical Statistics, vol. 22, no. 1, 215–228, 2013.
  • W. Kruijer, J. Rousseau, . others, Bayesian semi-parametric estimation of the long-memory parameter under FEXP-priors, Electronic Journal of Statistics, vol. 7, 2947–2969, 2013.
  • N. Chopin, J. Rousseau, B. Liseo, Computational aspects of Bayesian spectral density estimation, Journal of Computational and Graphical Statistics, vol. 22, no. 3, 533–557, 2013.

2012

  • V. Rivoirard, J. Rousseau, . others, Bernstein–von Mises theorem for linear functionals of the density, The Annals of Statistics, vol. 40, no. 3, 1489–1523, 2012.
  • V. Rivoirard, J. Rousseau, . others, Posterior concentration rates for infinite dimensional exponential families, Bayesian Analysis, vol. 7, no. 2, 311–334, 2012.
  • I. Albert, S. Donnet, C. Guihenneuc-Jouyaux, S. Low-Choy, K. Mengersen, J. Rousseau, . others, Combining expert opinions in prior elicitation, Bayesian Analysis, vol. 7, no. 3, 503–532, 2012.
  • J. Rousseau, N. Chopin, B. Liseo, . others, Bayesian nonparametric estimation of the spectral density of a long or intermediate memory Gaussian process, The Annals of Statistics, vol. 40, no. 2, 964–995, 2012.
  • O. Lieberman, R. Rosemarin, J. Rousseau, Asymptotic theory for maximum likelihood estimation of the memory parameter in stationary Gaussian processes, Econometric Theory, vol. 28, no. 2, 457–470, 2012.

2011

  • J. Rousseau, K. Mengersen, Asymptotic behaviour of the posterior distribution in overfitted mixture models, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol. 73, no. 5, 689–710, 2011.

2010

  • W. Kruijer, J. Rousseau, A. Van Der Vaart, . others, Adaptive Bayesian density estimation with location-scale mixtures, Electronic Journal of Statistics, vol. 4, 1225–1257, 2010.
  • J. Rousseau, . others, Rates of convergence for the posterior distributions of mixtures of betas and adaptive nonparametric estimation of the density, The Annals of Statistics, vol. 38, no. 1, 146–180, 2010.
  • D. Gajda, C. Guihenneuc-Jouyaux, J. Rousseau, K. Mengersen, D. Nur, . others, Use in practice of importance sampling for repeated MCMC for Poisson models, Electronic journal of statistics, vol. 4, 361–383, 2010.

2009

  • C. P. Robert, N. Chopin, J. Rousseau, . others, Harold Jeffreys’s theory of probability revisited, Statistical Science, vol. 24, no. 2, 141–172, 2009.
  • R. Mcvinish, J. Rousseau, K. Mengersen, Bayesian goodness of fit testing with mixtures of triangular distributions, Scandinavian Journal of Statistics, vol. 36, no. 2, 337–354, 2009.
  • D. Nur, D. Allingham, J. Rousseau, K. L. Mengersen, R. McVinish, Bayesian hidden Markov model for DNA sequence segmentation: A prior sensitivity analysis, Computational Statistics & Data Analysis, vol. 53, no. 5, 1873–1882, 2009.

2008

  • I. Albert, E. Grenier, J. Denis, J. Rousseau, Quantitative Risk Assessment from Farm to Fork and Beyond: A Global Bayesian Approach Concerning Food-Borne Diseases, Risk Analysis, vol. 28, no. 2, 557–571, 2008.
  • D. Fraser, J. Rousseau, Studentization and deriving accurate p-values, Biometrika, vol. 95, no. 1, 1–16, 2008.
  • A. Chambaz, J. Rousseau, Bounds for Bayesian order identification with application to mixtures, The Annals of Statistics, 938–962, 2008.
  • S. J. Low Choy, K. L. Mengersen, J. Rousseau, Encoding expert opinion on skewed non-negative distributions, Journal of Applied Probability and Statistics, vol. 3, no. 1, 1–21, 2008.

2007

  • J. Rousseau, Approximating interval hypothesis: p-values and Bayes factors, Bayesian statistics, vol. 8, 417–452, 2007.

2005

  • G. Gayraud, J. Rousseau, Rates of convergence for a Bayesian level set estimation, Scandinavian journal of statistics, vol. 32, no. 4, 639–660, 2005.
  • C. Guihenneuc-Jouyaux, J. Rousseau, Laplace expansions in Markov chain Monte Carlo algorithms, Journal of Computational and Graphical Statistics, vol. 14, no. 1, 75–94, 2005.

2004

  • P. Müller, G. Parmigiani, C. Robert, J. Rousseau, Optimal sample size for multiple testing: the case of gene expression microarrays, Journal of the American Statistical Association, vol. 99, no. 468, 990–1001, 2004.

2003

  • O. Lieberman, J. Rousseau, D. M. Zucker, . others, Valid asymptotic expansions for the maximum likelihood estimator of the parameter of a stationary, Gaussian, strongly dependent process, The Annals of Statistics, vol. 31, no. 2, 586–612, 2003.

2002

  • A. Philippe, J. Rousseau, . others, Non-informative priors in the case of Gaussian long-memory processes, Bernoulli, vol. 8, no. 4, 451–473, 2002.
  • J. Rousseau, Asymptotic properties of HPD regions in the discrete case, Journal of multivariate analysis, vol. 83, no. 1, 1–21, 2002.

2001

  • O. Lieberman, J. Rousseau, D. M. Zucker, Valid Edgeworth expansion for the sample autocorrelation function under long range dependence, Econometric Theory, vol. 17, no. 1, 257–275, 2001.
  • J. Rousseau, M. Ghosh, D. Kim, Non-informative priors for the bivariate Fieller-Creasy problem, Statistics and Decisions, vol. 19, 227, 2001.

2000

  • O. Lieberman, J. Rousseau, D. M. Zucker, Small-sample likelihood-based inference in the ARFIMA model, Econometric theory, vol. 16, no. 2, 231–248, 2000.
  • J. Rousseau, Coverage properties of one-sided intervals in the discrete case and application to matching priors, Annals of the Institute of Statistical Mathematics, vol. 52, no. 1, 28–42, 2000.