Catherine Matias
Catherine Matias
CNRS, Université Pierre et Marie Curie, COSTNET CA15109
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Identifiability of parameters in latent structure models with many observed variables
ES Allman, C Matias, JA Rhodes
The Annals of Statistics 37 (6A), 3099-3132, 2009
Statistical clustering of temporal networks through a dynamic stochastic block model
C Matias, V Miele
arXiv preprint arXiv:1506.07464, 2015
Asymptotics of the maximum likelihood estimator for general hidden Markov models
R Douc, C Matias
Bernoulli 7 (3), 381-420, 2001
Minimax estimation of the noise level and of the deconvolution density in a semiparametric convolution model
C Butucea, C Matias
Bernoulli 11 (2), 309-340, 2005
Modeling heterogeneity in random graphs through latent space models: a selective review
C Matias, S Robin
ESAIM: Proceedings and Surveys 47, 55-74, 2014
Inferring sparse Gaussian graphical models with latent structure
C Ambroise, J Chiquet, C Matias
Electronic Journal of Statistics 3, 205-238, 2009
New consistent and asymptotically normal parameter estimates for random‐graph mixture models
C Ambroise, C Matias
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2012
Simone: Statistical inference for modular networks
J Chiquet, A Smith, G Grasseau, C Matias, C Ambroise
Bioinformatics 25 (3), 417-418, 2009
Parameter identifiability in a class of random graph mixture models
ES Allman, C Matias, JA Rhodes
Journal of Statistical Planning and Inference 141 (5), 1719-1736, 2011
Convergence of the groups posterior distribution in latent or stochastic block models
M Mariadassou, C Matias
Bernoulli 21 (1), 537-573, 2015
A semiparametric extension of the stochastic block model for longitudinal networks
C Matias, T Rebafka, F Villers
Biometrika 105 (3), 665-680, 2018
Cophylogeny reconstruction via an approximate Bayesian computation
C Baudet, B Donati, B Sinaimeri, P Crescenzi, C Gautier, C Matias, ...
Systematic Biology 64 (3), 416-431, 2015
Semiparametric deconvolution with unknown noise variance
C Matias
ESAIM: Probability and Statistics 6, 271-292, 2002
Network motifs: mean and variance for the count
C Matias, S Schbath, E Birmelé, JJ Daudin, S Robin
REVSTAT-Statistical Journal 4 (1), 31-51, 2006
Adaptivity in convolution models with partially known noise distribution
C Butucea, C Matias, C Pouet
Electronic Journal of Statistics 2, 897-915, 2008
Adaptive goodness-of-fit testing from indirect observations
C Butucea, C Matias, C Pouet
Annales de l'IHP Probabilités et statistiques 45 (2), 352-372, 2009
Maximum likelihood estimator consistency for a ballistic random walk in a parametric random environment
F Comets, M Falconnet, O Loukianov, D Loukianova, C Matias
Stochastic Processes and their Applications 124 (1), 268-288, 2014
Exact adaptive estimation of the shape of a periodic function with unknown period corrupted by white noise
I Castillo, C Lévy-Leduc, C Matias
Mathematical methods of statistics 15 (2), 146-175, 2006
On efficient estimators of the proportion of true null hypotheses in a multiple testing setup
VH Nguyen, C Matias
Scandinavian Journal of Statistics 41 (4), 1167-1194, 2014
Asymptotic normality and efficiency of the maximum likelihood estimator for the parameter of a ballistic random walk in a random environment
M Falconnet, D Loukianova, C Matias
Mathematical Methods of Statistics 23 (1), 1-19, 2014
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