My office

UPMC - Site Jussieu
Tours 15-16, Bureau 212 (2ème étage)

Address

Université Pierre et Marie Curie
Case courrier 188
4 place Jussieu
75252 PARIS Cedex 05, FRANCE

Contact


+33 (0)1 44 27 70 43

Research

Research themes


Publications

Preprints
  1. Ana Arribas-Gil & Catherine Matias, A time warping approach to multiple sequence alignment. HAL preprint.
  2. Catherine Matias, Tabea Rebafka & Fanny Villers, A semiparametric extension of the stochastic block model for longitudinal networks HAL preprint, R code available on request.

Publications in journals
  1. Catherine Matias & Vincent Miele, Statistical clustering of temporal networks through a dynamic stochastic block model. To appear in the Journal of the Royal Statistical Society: Series B. Journal link , HAL preprint, R package dynSBM.
  2. Pierre Andreoletti, Dasha Loukianova & Catherine Matias, Parametric estimation of a one-dimensional ballistic random walk in a Markov environment. ESAIM Prob. & Stat.19: 605-625, 2015. Journal link, HAL preprint.
  3. C. Baudet, B. Donati, B. Sinaimeri, P. Crescenzi, C. Gautier, C. Matias & M-F. Sagot, Co-phylogeny reconstruction via an approximate Bayesian computation. Systematic Biology. 64(3): 416-431, 2015. Journal link, Software.
  4. Mahendra Mariadassou & Catherine Matias, Groups posterior distribution in latent or stochastic block models for matrices. Bernoulli, 21(1):537-573, 2015. Hal preprint, Journal link.
  5. Catherine Matias & Stéphane Robin, Modeling heterogeneity in random graphs through latent space models: a selective review. Esaim Proc. & Surveys, 47: 55-74, 2014. Journal link.
  6. Mikael Falconnet, Dasha Loukianova & Catherine Matias, Asymptotic normality and efficiency of the maximum likelihood estimator for the parameter of a ballistic random walk in a random environment. Mathematical Methods of Statistics. 23(1) :1-19, 2014. Hal preprint , Journal link.
  7. Francis Comets, Mikael Falconnet, Oleg Loukianov, Dasha Loukianova & Catherine Matias, Maximum likelihood estimator consistency for ballistic random walk in a parametric random environment. Stochastic Processes & Applications. 124(1) : 268-288, 2014. Hal preprint, Journal link.
  8. Van Hanh Nguyen & Catherine Matias, On efficient estimators of the proportion of true null hypotheses in a multiple testing setup. Scandinavian Journal of Statistics, 41(4): 1167-1194, 2014. Hal preprint, Journal link.
  9. Van Hanh Nguyen & Catherine Matias, Nonparametric estimation of the density of the alternative hypothesis in a multiple testing setup. Application to local false discovery rate estimation. ESAIM Prob. & Stat.. 18: 584-612, 2014. Hal preprint , Journal link.
  10. Ana Arribas-Gil & Catherine Matias, A context dependent pair hidden Markov model for statistical alignment. Statistical Applications in Genetics and Molecular Biology, 11(1), Article 5, 2012. Hal preprint , Journal link.
  11. Christophe Ambroise & Catherine Matias, New consistent and asymptotically normal parameter estimates for random graph mixture models. Journal of the Royal Statistical Society: Series B, 74(1): 3-35, 2012. pdf link , Journal link
  12. Elizabeth Allman, Catherine Matias & John Rhodes, Parameters identifiability in a class of random graph mixture models. Journal of Statistical Planning and Inference, 141: 1719-1736, 2011. Arxiv preprint, Journal link.
  13. Elizabeth Allman, Catherine Matias & John Rhodes, Identifiability of parameters in latent structure models with many observed variables. Annals of Statistics, 37(6A): 3099-3132, 2009. Journal link.
  14. Julien Chiquet, Alexander Smith, Gilles Grasseau, Catherine Matias & Christophe Ambroise, SIMoNe : Statistical Inference for MOdular NEtworks. Bioinformatics, 25(3): 417-418, 2009. Journal link, R package.
  15. Christophe Ambroise, Julien Chiquet & Catherine Matias, Penalized maximum likelihood inference for sparse Gaussian graphical models with hidden structure. Electronic Journal of Statistics, 3: 205-238, 2009. Journal link.
  16. Antoine Chambaz & Catherine Matias, Number of hidden states and memory: a joint order estimation problem for Markov chains with Markov regime. ESAIM Probab. & Stat., 13: 38-50, 2009. Journal link.
  17. Cristina Butucea, Catherine Matias & Christophe Pouet, Adaptive goodness-of-fit testing from indirect observations. Annales de l'Institut Henri Poincaré, 45(2): 352-372, 2009. Journal link.
  18. Cristina Butucea, Catherine Matias & Christophe Pouet, Adaptivity in convolution models with partially known noise distribution. Electronic Journal of Statistics, 2: 897-915, 2008. Journal link.
  19. Ana Arribas-Gil, Élisabeth Gassiat & Catherine Matias, Parameter estimation in pair hidden Markov models. Scandinavian Journal of Statistics, 33(4): 651-671, 2006. Arxiv preprint , Journal link.
  20. Catherine Matias, Sophie Schbath, Étienne Birmelé, Jean-Jacques Daudin & Stéphane Robin, Networks motifs : mean and variance for the count. Revstat, 4(1): 31-51, 2006. Journal link.
  21. Ismaël Castillo, Céline Lévy-Leduc & Catherine Matias, Exact adaptive estimation of the shape of a periodic function with unknown period corrupted by white noise. Mathematical Methods of Statistics, 15(2): 146-175, 2006. pdf link.
  22. Cristina Butucea & Catherine Matias, Minimax estimation of the noise level and of the deconvolution density in a semiparametric convolution model. Bernoulli, 11(2): 309-340, 2005. Journal link.
  23. Catherine Matias & Marie-Luce Taupin, Minimax estimation of linear functionals in the convolution model. Mathematical Methods of Statistics, 13(3): 282-328, 2004. pdf link.
  24. Catherine Matias, Semiparametric deconvolution with unknown noise variance. ESAIM Probab. & Stat., 6: 271-292, 2002. Journal link
  25. Randal Douc & Catherine Matias, Asymptotics of the maximum likelihood estimator for general hidden Markov models. Bernoulli, 7(3): 381-420, 2001. Journal link.

Unpublished manuscripts (in french)

(Some) Conference Slides


PhD Students

Present
Past

Teaching

2016-2017

Previous


Responsibilities


Others links/info

Seminars

Journals / Bibliography

Others (maths related)

Climbing