Profil

BARAUD Yannick

University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Mathematics (DMATH)

Main Referenced Co-authors
Birgé, Lucien (4)
Huet, Sylvie (4)
Birgé, L. (3)
Comte, F. (2)
Giraud, Christophe (2)
Main Referenced Keywords
robust estimation (2); Bayes procedure (1); Bayesian estimation (1); Density Estimation (1); Density estimation (1);
Main Referenced Disciplines
Mathematics (30)

Publications (total 30)

The most downloaded
298 downloads
Baraud, Y., Nourdin, I., & Peccati, G. (2020). Estimating the number of infected persons. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/43287. https://hdl.handle.net/10993/43287

The most cited

98 citations (Scopus®)

Baraud, Y. (2002). Non-asymptotic minimax rates of testing in signal detection. Bernoulli, 8 (5), 577--606. https://hdl.handle.net/10993/40202

Baraud, Y. (2023). From robust tests to Bayes-like posterior distributions. Probability Theory and Related Fields. doi:10.1007/s00440-023-01222-8
Peer Reviewed verified by ORBi

Baraud, Y., Halconruy, H., & Maillard, G. (2022). Robust density estimation with the L1-loss. Applications to the estimation of a density on the line satisfying a shape constraint. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/51513.

Baraud, Y. (2021). Tests and estimation strategies associated to some loss functions. Probability Theory and Related Fields, 180 (3), 799-846. doi:10.1007/s00440-021-01065-1
Peer Reviewed verified by ORBi

Baraud, Y., & Chen, J. (2020). Robust Estimation of a Regression Function in Exponential Families. (1). ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/44605.

Baraud, Y., Nourdin, I., & Peccati, G. (2020). Estimating the number of infected persons. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/43287.

Baraud, Y., & Birgé, L. (2020). ROBUST BAYES-LIKE ESTIMATION: RHO-BAYES ESTIMATION. Annals of Statistics. doi:10.1214/20-AOS1948
Peer Reviewed verified by ORBi

Baraud, Y. (2019). Can we trust L2-criteria and L2-losses? Journal de la Société Française de Statistique, 160 (3).
Peer reviewed

Baraud, Y., & Birgé, L. (2018). Rho-estimators revisited: general theory and applications. Annals of Statistics, 46 (6B), 3767--3804. doi:10.1214/17-AOS1675
Peer reviewed

Baraud, Y., Birgé, L., & Sart, M. (2017). A new method for estimation and model selection: $\rho$-estimation. Inventiones Mathematicae, 207 (2), 425--517. doi:10.1007/s00222-016-0673-5
Peer reviewed

Baraud, Y., & Birgé, L. (2017). Une alternative robuste au maximum de vraisemblance: la $\rho$-estimation. Journal de la Société Française de Statistique, 158 (3), 1--26.
Peer reviewed

Baraud, Y. (2016). Bounding the expectation of the supremum of an empirical process over a (weak) VC-major class. Electronic Journal of Statistics, 10 (2), 1709--1728. doi:10.1214/15-EJS1055
Peer Reviewed verified by ORBi

Baraud, Y., & Birgé, L. (2016). Rho-estimators for shape restricted density estimation. Stochastic Processes and Their Applications, 126 (12), 3888--3912. doi:10.1016/j.spa.2016.04.013
Peer reviewed

Baraud, Y., Giraud, C., & Huet, S. (2014). Estimator selection in the Gaussian setting. Ann. Inst. Henri Poincaré Probab. Stat, 50 (3), 1092--1119. doi:10.1214/13-AIHP539
Peer reviewed

Baraud, Y., & Birgé, L. (2014). Estimating composite functions by model selection. Ann. Inst. Henri Poincaré Probab. Stat, 50 (1), 285--314. doi:10.1214/12-AIHP516
Peer reviewed

Baraud, Y. (2013). Estimation of the density of a determinantal process. Confluentes Mathematici, 5 (1), 3--21. doi:10.5802/cml.1
Peer Reviewed verified by ORBi

Baraud, Y. (2011). Estimator selection with respect to Hellinger-type risks. Probab. Theory Related Fields, 151 (1-2), 353--401. doi:10.1007/s00440-010-0302-y
Peer reviewed

Baraud, Y. (2010). A Bernstein-type inequality for suprema of random processes with applications to model selection in non-Gaussian regression. Bernoulli, 16 (4), 1064--1085. doi:10.3150/09-BEJ245
Peer reviewed

Baraud, Y., & Birgé, L. (2009). Estimating the intensity of a random measure by histogram type estimators. Probab. Theory Related Fields, 143 (1-2), 239--284. doi:10.1007/s00440-007-0126-6
Peer reviewed

Baraud, Y., Giraud, C., & Huet, S. (2009). Gaussian model selection with an unknown variance. Annals of Statistics, 37 (2), 630--672. doi:10.1214/07-AOS573
Peer reviewed

Baraud, Y., Huet, S., & Laurent, B. (2005). Testing convex hypotheses on the mean of a Gaussian vector. Application to testing qualitative hypotheses on a regression function. Annals of Statistics, 33 (1), 214--257. doi:10.1214/009053604000000896
Peer reviewed

Baraud, Y. (2004). Confidence balls in Gaussian regression. Annals of Statistics, 32 (2), 528--551. doi:10.1214/009053604000000085
Peer reviewed

Baraud, Y., Huet, S., & Laurent, B. (2003). Adaptive tests of qualitative hypotheses. ESAIM: Probability and Statistics, 7, 147--159. doi:10.1051/ps:2003006
Peer reviewed

Baraud, Y., Huet, S., & Laurent, B. (2003). Adaptive tests of linear hypotheses by model selection. Annals of Statistics, 31 (1), 225--251. doi:10.1214/aos/1046294463
Peer reviewed

Baraud, Y. (2002). Habilitation Thesis [Postdoctoral thesis & other thesis, Université Paris XI Orsay]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/40209

Baraud, Y. (2002). Non-asymptotic minimax rates of testing in signal detection. Bernoulli, 8 (5), 577--606.
Peer reviewed

Baraud, Y., Huet, S., & Laurent, B. (2002). A new test of linear hypothesis in regression. In Goodness-of-fit tests and model validity (Paris, 2000) (pp. 195--207). Birkhäuser Boston, Boston, MA.
Peer reviewed

Baraud, Y. (2002). Model selection for regression on a random design. ESAIM: Probability and Statistics, 6, 127--146. doi:10.1051/ps:2002007
Peer reviewed

Baraud, Y., Comte, F., & Viennet, G. (2001). Model selection for (auto-)regression with dependent data. ESAIM: Probability and Statistics, 5, 33--49. doi:10.1051/ps:2001101
Peer reviewed

Baraud, Y., Comte, F., & Viennet, G. (2001). Adaptive estimation in autoregression or $\beta$-mixing regression via model selection. Annals of Statistics, 29 (3), 839--875. doi:10.1214/aos/1009210692
Peer reviewed

Baraud, Y. (2000). Model selection for regression on a fixed design. Probab. Theory Related Fields, 117 (4), 467--493. doi:10.1007/PL00008731
Peer reviewed

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