Stéphane Girard Senior research scientist at Inria Grenoble Rhône-Alpes.

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Home Publications Working papers Communications Software PhD students Projects Dissemination

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This page lists my published journal papers and book chapters. If you are interested in the corresponding pdf, please select one of these topics Statistics of extremes, High dimensional statistical learning, Functional estimation or Applications of statistics. Conference papers, with (sometimes) the associated slides are listed in the communications page.





[147] S. Girard, T. Opitz & A. Usseglio-Carleve. "ANOVEX: ANalysis of Variability for heavy-tailed EXtremes", Electronic Journal of Statistics, to appear, 2024.

[146] M. Allouche, S. Girard & E. Gobet, "Learning extreme Expected Shortfall and Conditional Tail Moments with neural networks. Application to cryptocurrency data", Neural Networks, 182, 106903, 2025.

[145] J. Arbel, S.Girard & H. Lorenzo, "Shrinkage for Extreme Partial Least Squares", Statistics and Computing, 34, 181, 2024.

[144] M. Allouche, J. El-methni & S. Girard, "Reduced-bias estimation of the extreme conditional tail expectation for Box-Cox transforms of heavy-tailed distributions", Journal of Statistical Planning and Inference, 233, 106189, 2024.

[143] J. El Methni & S. Girard. "A refined extreme quantile estimator for Weibull tail-distributions", REVSTAT - Statistical Journal, to appear, 2024.

[142] M. Allouche, S. Girard & E. Gobet, "Estimation of extreme quantiles from heavy-tailed distributions with neural networks", Statistics and Computing, 34, 12, 2024.

[141] T. Moins, J. Arbel, A. Dutfoy & S. Girard. "On the use of a local Rhat to improve MCMC convergence", Bayesian Analysis, to appear, 2024.

[140] T. Moins, J. Arbel, S. Girard & A. Dutfoy. "Reparameterization of extreme value framework for improved Bayesian workflow", Computational Statistics and Data Analysis, 187, 107807, 2023.

[139] R. Barbero, S. Girard, T. Opitz & A. Usseglio-Carleve, "Les statistiques de l'extrême", Pour la Science, 546, 14--16, 2023.

[138] M. Allouche, J. El-methni & S. Girard. "A refined Weissman estimator for extreme quantiles", Extremes, 26, 545--572, 2023.

[137] J. Arbel, S. Girard, H. Nguyen & A. Usseglio-Carleve, "Multivariate expectile-based distribution: properties, Bayesian inference, and applications", Journal of Statistical Planning and Inference, 225, 146--170, 2023.

[136] M. Bousebata, G. Enjolras & S. Girard, "Extreme Partial Least-Squares", Journal of Multivariate Analysis, 194, 105101, 2023.

[135] A. Constantin, M. Fauvel & S. Girard, "Mixture of multivariate Gaussian processes for classification of irregularly sampled satellite image time-series", Statistics and Computing, 32, 79, 2022.

[134] S. Girard, G. Stupfler & A. Usseglio-Carleve, "On automatic bias reduction for extreme expectile estimation", Statistics and Computing, 32, 64, 2022.

[133] M. Allouche, S. Girard & E. Gobet, "EV-GAN: Simulation of extreme events with ReLU neural networks", Journal of Machine Learning Research, 23(150), 1--39, 2022.

[132] M. Allouche, S. Girard & E. Gobet, "Generative model for fBm with deep ReLU neural networks", Journal of Complexity, 73, 101667, 2022.

[131] S. Girard, H. Lorenzo & J. Saracco, "Advanced topics in Sliced Inverse Regression", Journal of Multivariate Analysis, 188, 104852, 2022.

[130] S. Girard, G. Stupfler & A. Usseglio-Carleve, "Functional estimation of extreme conditional expectiles", Econometrics and Statistics, 21, 131--158, 2022.

[129] A. Constantin, M. Fauvel & S. Girard, "Joint supervised classification and reconstruction of irregularly sampled satellite image times series", IEEE Transactions on Geoscience and Remote Sensing, 60, 1--13, 2022.

[128] S. Girard, G. Stupfler & A. Usseglio-Carleve, "Nonparametric extreme conditional expectile estimation", Scandinavian Journal of Statistics, 49, 78--115, 2022.

[127] S. Girard, G. Stupfler & A. Usseglio-Carleve, "Extreme conditional expectile estimation in heavy-tailed heteroscedastic regression models", Annals of Statistics, 49(6), 3358--3382, 2021.

[126] L. Gardes & S. Girard, "On the estimation of the variability in the distribution tail", Test, 30, 884--907, 2021.

[125] T. Moins, J. Arbel, A. Dutfoy & S. Girard, "Discussion of the paper 'Rank-Normalization, Folding, and Localization: An Improved Rhat for Assessing Convergence of MCMC'", Bayesian Analysis, 16(2), 711--712, 2021.

[124] S. Girard, G. Stupfler & A. Usseglio-Carleve, "Extreme Lp-quantile kernel regression", In Advances in Contemporary Statistics and Econometrics, A. Daouia and A. Ruiz-Gazen (eds.), Springer, 197--219, 2021.

[123] A. Daouia, S. Girard & G. Stupfler, "ExpectHill estimation, extreme risk and heavy tails", Journal of Econometrics, 221(1), 97--117, 2021.

[122] M. Vladimirova, S. Girard, N. Hien & J. Arbel. "Sub-Weibull distributions: generalizing sub-Gaussian and sub-Exponential properties to heavier-tailed distributions", Stat, 9, e318, 2020.

[121] M. Stehlik, J. Kiselak, M. Vaciulis, P. Jordanova, L.N. Soza, Z. Fabian, P. Hermann, L. Strelec, A. Rivera, S. Girard & S. Torres, "Priority statement and some properties of t-lgHill estimator", Extremes, 23, 493--499, 2020.

[120] A. Ahmad, E. Deme, A. Diop, S. Girard & A. Usseglio-Carleve. "Estimation of extreme quantiles from heavy-tailed distributions in a location-dispersion regression model", Electronic Journal of Statistics, 14, 4421--4456, 2020.

[119] L. Gardes, S. Girard & G. Stupfler, "Beyond tail median and conditional tail expectation: extreme risk estimation using tail Lp-optimisation", Scandinavian Journal of Statistics, 47, 922--949, 2020.

[118] C. Albert, A. Dutfoy & S. Girard. "Asymptotic behavior of the extrapolation error associated with the estimation of extreme quantiles", Extremes, 23, 349--380, 2020.

[117] C. Albert, A. Dutfoy, L.Gardes & S. Girard. "An extreme quantile estimator for the log-generalized Weibull-tail model", Econometrics and Statistics, 13, 137--174, 2020.

[116] A. Daouia, S. Girard & G. Stupfler, "Tail expectile process and risk assessment", Bernoulli, 26, 531--556, 2020.

[115] J. Arbel, M. Crispino & S. Girard. "Dependence properties and Bayesian inference for asymmetric multivariate copulas", Journal of Multivariate Analysis, 174, 104530, 2019.

[114] A. Ag Ahmad, E. Deme, A. Diop & S. Girard. "Estimation of the tail-index in a conditional location-scale family of heavy-tailed distributions", Dependence Modeling, 7, 394--417, 2019.

[113] A. Daouia, S. Girard & G. Stupfler. "Extreme M-quantiles as risk measures: From L1 to Lp optimization", Bernoulli, 25, 264--309, 2019.

[112] J. El Methni, L. Gardes & S. Girard. "Kernel estimation of extreme regression risk measures", Electronic Journal of Statistics, 12, 359--398, 2018.

[111] S. Girard. "Transformation of a copula using the associated co-copula", Dependence Modeling, 6, 298--308, 2018.

[110] A. Daouia, S. Girard & G. Stupfler. "Estimation of Tail Risk based on Extreme Expectiles", Journal of the Royal Statistical Society series B, 80, 262--292, 2018.

[109] O. Chelly, L. Amsaleg, T. Furon, S. Girard, M. Houle, K. Kawarabayashi & M. Nett. "Extreme-Value-Theoretic Estimation of Local Intrinsic Dimensionality", Journal of Data Mining and Knowledge Discovery, 32 (6), 1768--1805, 2018.

[108] M. Lopes, M. Fauvel, A. Ouin & S. Girard. "Spectro-temporal heterogeneity measures from dense high spatial resolution satellite image time series: Application to grassland species diversity estimation", Remote Sensing, 9 (10), 2017.

[107] A. Chiancone, F. Forbes & S. Girard. "Student Sliced Inverse Regression", Computational Statistics and Data Analysis, 113, 441--456, 2017.

[106] M. Lopes, M. Fauvel, S. Girard & D. Sheeren. "Object-based classification from high resolution satellite image time series with Gaussian mean map kernels: Application to grassland management practices", Remote Sensing, 9 (7), 2017.

[105] A. Chiancone, S. Girard & J. Chanussot. "Collaborative Sliced Inverse Regression", Communications in Statistics - Theory and Methods, 46, 6035--6053, 2017.

[104] M. Fauvel, S. Girard, S. Douté & L. Gardes. "Machine learning methods for the inversion of hyperspectral images", In A. Reimer, editor, Horizons in World Physics, p. 51-77, Nova Science, New-York, 2017.

[103] S. Girard & G. Stupfler. "Intriguing properties of extreme geometric quantiles", REVSTAT - Statistical Journal, 15, 107--139, 2017.

[102] M. Stehlik, P. Aguirre, S. Girard, P. Jordanova, J. Kiselák, S. Torres-Leiva, Z. Sadovsky & A. Rivera. "On ecosystems dynamics", Ecological Complexity, 29, 10--29, 2017.

[101] B. Barroca, P. Bernardara, S. Girard & G. Mazo. "Considering hazard estimation uncertain in urban resilience strategies", In K. Etingoff, editor, Ecological Resilience, Response to Climate Change and Natural Disasters, 197--220, Apple Academic Press, 2016.

[100] P. Jordanova, Z. Fabian, P. Hermann, L. Strelec, A. Rivera, S. Girard, S. Torres-Leiva & M. Stehlik. "Weak properties and robustness of t-Hill estimators", Extremes, 19, 591--626, 2016.

[99] S. Girard & J. Saracco. "Supervised and unsupervised classification using mixture models" In D. Fraix-Burnet and S. Girard, editors, Statistics for astrophysics, clustering and classification, volume 77, pages 69--90, EDP Sciences, 2016.

[98] G. Mazo, S. Girard & F. Forbes. "A flexible and tractable class of one-factor copulas", Statistics and Computing, 26, 965--979, 2016.

[97] L. Gardes & S. Girard. "On the estimation of the functional Weibull tail-coefficient", Journal of Multivariate Analysis, 146, 24--45, 2016.

[96] F. Durante, S. Girard & G. Mazo, "Marshall-Olkin type copulas generated by a global shock", Journal of Computational and Applied Mathematics, 296, 638--648, 2016.

[95] G. Mazo, S. Girard & F. Forbes, "Weighted least square inference based on dependence coefficients for multivariate copulas", ESAIM: Probability and Statistics, 19, 746--765, 2015.

[94] M. Fauvel, C. Bouveyron & S. Girard. "Parsimonious Gaussian process models for the classification of hyperspectral remote sensing images", IEEE Geoscience and Remote Sensing Letters, 12, 2423--2427, 2015.

[93] S. Sylla, S. Girard, A. Diongue, A. Diallo & C. Sokhna. "A classification method for binary predictors combining similarity measures and mixture models", Dependence Modeling, 3, 240--255, 2015.

[92] S. Girard & G. Stupfler. "Extreme geometric quantiles in a multivariate regular variation framework", Extremes, 18, 629--663, 2015.

[91] G. Mazo, S. Girard & F. Forbes. "A class of multivariate copulas based on products of bivariate copulas", Journal of Multivariate Analysis, 140, 363--376, 2015.

[90] C. Bouveyron, M. Fauvel & S. Girard. "Kernel discriminant analysis and clustering with parsimonious Gaussian process models", Statistics and Computing, 25,1143--1162, 2015.

[89] L. Gardes & S. Girard. "Nonparametric estimation of the conditional tail copula", Journal of Multivariate Analysis, 137, 1--16, 2015.

[88] S. Girard & S. Louhichi. "On the strong consistency of the kernel estimator of extreme conditional quantiles", In E. Ould-Said et al, editors, Functional Statistics and Applications, Springer, pages 59--77, 2015.

[87] F. Durante, S. Girard & G. Mazo. "Copulas based on Marshall-Olkin machinery", In U. Cherubini et al, editors, Marshall-Olkin Distributions. Advances in Theory and Applications, volume 141 of Springer Proceedings in Mathematics and Statistics, pages 15--31, Springer, 2015.

[86] J. El Methni, L. Gardes & S. Girard. "Estimation de mesures de risque pour des pluies extrêmes dans la région Cévennes Vivarais", La Houille Blanche, 4, 26--31, 2015.

[85] E. Deme, A. Guillou & S. Girard. "Reduced-biased estimators of the Conditional Tail Expectation for heavy-tailed distributions" In M. Hallin et al, editors, Mathematical Statistics and Limit Theorems, pages 105--123, Springer, 2015.

[84] B. Barroca, P. Bernardara, S. Girard & G. Mazo. "Considering hazard estimation uncertain in urban resilience strategies", Natural Hazards and Earth System Sciences, 15, 25--34, 2015.

[83] S. Girard and J. Saracco. "An introduction to dimension reduction in nonparametric kernel regression" In D. Fraix-Burnet and D. Valls-Gabaud, editors, Regression methods for astrophysics, volume 66, pages 167--196, EDP Sciences, 2014.

[82] A. Nazin & S. Girard. "L1-optimal linear programming estimator for periodic frontier functions with Holder continuous derivative", Automation and Remote Control, 75(12), 2152--2169, 2014.

[81] J. El Methni, L. Gardes & S. Girard. "Nonparametric estimation of extreme risks from conditional heavy-tailed distributions", Scandinavian Journal of Statistics, 41, 988--1012, 2014.

[80] M. Chavent, S. Girard, V. Kuentz, B. Liquet, T.M.N. Nguyen & J. Saracco. "A sliced inverse regression approach for data stream", Computational Statistics, 29, 1129--1152, 2014.

[79] S. Girard, A. Guillou & G. Stupfler. "Uniform strong consistency of a frontier estimator using kernel regression on high order moments", ESAIM: Probability and Statistics, 18, 642--666, 2014.

[78] R. Coudret, S. Girard, & J. Saracco. "A new sliced inverse regression method for multivariate response", Computational Statistics and Data Analysis, 77, 285--299, 2014.

[77] A. Daouia, S. Girard & A. Guillou. "A Gamma-moment approach to monotonic boundaries estimation: with applications in econometric and nuclear fields", Journal of Econometrics, 178, 727--740, 2014.

[76] A. Daouia, L. Gardes & S. Girard. "On kernel smoothing for extremal quantile regression", Bernoulli, 19, 2557--2589, 2013.

[75] E. Deme, L. Gardes & S. Girard. "On the estimation of the second order parameter for heavy-tailed distributions", REVSTAT - Statistical Journal, 11, 277--299,2013.

[74] L. Gardes & S. Girard. "Estimation de quantiles extrêmes pour les lois à queue de type Weibull : une synthèse bibliographique", Journal de la Société Française de Statistique, 154, 98--118, 2013.

[73] S. Girard, A. Guillou & G. Stupfler. "Frontier estimation with kernel regression on high order moments", Journal of Multivariate Analysis, 116, 172--189, 2013.

[72] E. Deme, S. Girard & A. Guillou. "Reduced-bias estimator of the Proportional Hazard Premium for heavy-tailed distributions", Insurance: Mathematics and Economics, 52, 550--559, 2013.

[71] J.B. Durand, S. Girard, V. Ciriza & L. Donini. "Optimization of power consumption and user impact based on point process modeling of the request sequence", Journal of the Royal Statistical Society series C, 62, 151--165, 2013.

[70] J. Carreau, D. Ceresetti, E. Ursu, S. Anquetin, J.D. Creutin, L. Gardes, S. Girard & G. Molinié. "Evaluation of classical spatial-analysis schemes of extreme rainfall", Natural Hazards and Earth System Sciences, 12, 3229--3240, 2012.

[69] S. Girard, A. Guillou & G. Stupfler. "Estimating an endpoint with high order moments in the Weibull domain of attraction", Statistics and Probability Letters, 82, 2136--2144, 2012.

[68] J. El Methni, L. Gardes, S. Girard & A. Guillou. "Estimation of extreme quantiles from heavy and light tailed distributions", Journal of Statistical Planning and Inference, 142(10), 2735--2747, 2012.

[67] L. Gardes & S. Girard. "Functional kernel estimators of large conditional quantiles", Electronic Journal of Statistics, 6, 1715--1744, 2012.

[66] L. Bergé, C. Bouveyron & S. Girard. "HDclassif: An R package for model-based clustering and discriminant analysis of high-dimensional data", Journal of Statistical Software, 46(6), 1--29, 2012.

[65] A. Daouia, L. Gardes & S. Girard. "Nadaraya's estimates for large quantiles and free disposal support curves" In I. Van Keilegom and P. Wilson, editors, Exploring research frontiers in contemporary statistics and econometrics , pages 1--22, Springer, 2012.

[64] S. Girard, A. Guillou & G. Stupfler. "Estimating an endpoint with high order moments", Test, 21, 697--729, 2012.

[63] S. Joshi, A. Lombardot, P. Flatresse, C. D'Agostino, A. Juge, E. Beigne & S. Girard. "Statistical estimation of dominant physical parameters for leakage variability in 32nanometer CMOS under supply voltage variations", Journal of Low Power Electronics, 8:113--124, 2012.

[62] J. Carreau & S. Girard. "Spatial extreme quantile estimation using a weighted log-likelihood approach", Journal de la Société Française de Statistique, 152(3), 66--83, 2011.

[61] A. Daouia, L. Gardes, S. Girard & A. Lekina. "Kernel estimators of extreme level curves", Test, 20(2), 311--333, 2011.

[60] C. Bouveyron, G. Celeux & S. Girard "Intrinsic dimension estimation by maximum likelihood in isotropic probabilistic PCA", Pattern Recognition Letters, 32(14), 1706--1713, 2011.

[59] L. Gardes & S. Girard "Functional kernel estimators of conditional extreme quantiles" In F. Ferraty, editor, Recent advances in functional data analysis and related topics, pages 135--140, Springer, Physica-Verlag, 2011.

[58] L. Gardes, S. Girard & A. Guillou. "Weibull tail-distributions revisited: a new look at some tail estimators", Journal of Statistical Planning and Inference, 141(1), 429--444, 2011.

[57] J. Jacques, C. Bouveyron, S. Girard, O. Devos, L. Duponchel & C. Ruckebusch. "Gaussian mixture models for the classification of high-dimensional vibrational spectroscopy data", Journal of Chemometrics, 24, 719--727, 2010.

[56] L. Gardes & S. Girard. "Conditional extremes from heavy-tailed distributions: An application to the estimation of extreme rainfall return levels", Extremes, 13(2), 177--204, 2010.

[55] L. Gardes, S. Girard & A. Lekina. "Functional nonparametric estimation of conditional extreme quantiles", Journal of Multivariate Analysis, 101, 419--433, 2010.

[54] C. Bouveyron & S. Girard. "Classification supervisée et non supervisée des données de grande dimension, La revue Modulad, 40, 81--102, 2009.

[53] C. Bouveyron & S. Girard. "Robust supervised classification with mixture models: Learning from data with uncertain labels", Pattern Recognition, 42(11), 2649--2658, 2009.

[52] C. Bernard-Michel, S. Douté, M. Fauvel, L. Gardes & S. Girard. "Retrieval of Mars surface physical properties from OMEGA hyperspectral images using Regularized Sliced Inverse Regression", Journal of Geophysical Research - Planets, 114, E06005, 2009.

[51] S. Girard & P. Jacob. "Frontier estimation with local polynomials and high power-transformed data", Journal of Multivariate Analysis, 100, 1691--1705, 2009.

[50] C. Bernard-Michel, L. Gardes & S. Girard. "Gaussian Regularized Sliced Inverse Regression", Statistics and Computing, 19, 85--98, 2009.

[49] C. Amblard & S. Girard. "A new bivariate extension of FGM copulas", Metrika, 70, 1--17, 2009.

[48] J. Diebolt, L. Gardes, S. Girard & A. Guillou. "Bias-reduced estimators of the Weibull tail-coefficient", Test, 17, 311--331, 2008.

[47] L. Gardes & S. Girard. "A moving window approach for nonparametric estimation of the conditional tail index", Journal of Multivariate Analysis, 99, 2368--2388, 2008.

[46] C. Bernard-Michel, L. Gardes & S. Girard. "A Note on Sliced Inverse Regression with Regularizations", Biometrics, 64, 982--986, 2008.

[45] S. Girard & P. Jacob. "A note on extreme values and kernel estimators of sample boundaries", Statistics and Probability Letters, 78, 1634--1638, 2008.

[44] S. Girard & P. Jacob. "Frontier estimation via kernel regression on high power-transformed data", Journal of Multivariate Analysis, 99, 403--420, 2008.

[43] S. Girard & L. Menneteau. "Smoothed extreme value estimators of non-uniform point processes boundaries with application to star-shaped supports estimation", Communication in Statistics - Theory and Methods, 37(6), 881--897, 2008.

[42] L. Gardes & S. Girard. "Estimation of the Weibull tail-coefficient with linear combination of upper order statistics", Journal of Statistical Planning and Inference, 138, 1416--1427, 2008.

[41] J. Diebolt, L. Gardes, S. Girard & A. Guillou. "Bias-reduced extreme quantiles estimators of Weibull-tail distributions", Journal of Statistical Planning and Inference, 138, 1389--1401, 2008.

[40] S. Girard & S. Iovleff. "Auto-associative models, nonlinear Principal component analysis, manifolds and projection pursuit" In A. Gorban et al, editors, Principal Manifolds for Data Visualisation and Dimension Reduction, volume 28, p. 205-222, LNCSE, Springer-Verlag, 2007.

[39] C. Bouveyron, S. Girard & C. Schmid. "High Dimensional Data Clustering", Computational Statistics and Data Analysis, 52, 502--519, 2007.

[38] C. Bouveyron, S. Girard & C. Schmid. "High-dimensional discriminant Analysis", Communication in Statistics - Theory and Methods, 36(14), 2607--2623, 2007.

[37] J. Diebolt, M. Garrido & S. Girard "A goodness-of-fit test for the distribution tail" In M. Ahsanulah and S. Kirmani, editors, Extreme value distributions, p. 95-109, Nova Science, New-York, 2007.

[36] C. Bouveyron, S. Girard & C. Schmid. "Class-specific subspace discriminant analysis for high-dimensional data", In C. Saunders et al., editors, Lecture Notes in Computer Science, volume 3940, p. 139-150. Springer-Verlag, Berlin Heidelberg, 2006.

[35] J. Geffroy, S. Girard & P. Jacob. "Asymptotic normality of the L1-error of a boundary estimate", Nonparametric Statistics, 18(1), 21-31, 2006.

[34] L. Gardes & S. Girard. "Comparison of Weibull tail-coefficient estimators", REVSTAT - Statistical Journal, 4(2), 163-188, 2006.

[33] L. Gardes & S. Girard. "Asymptotic properties of a Pickands type estimator of the extreme value index", In Louis R. Velle, editor, Focus on probability theory, Nova Science, New-York, 133-149, 2006.

[32] J. Diebolt, M. El-Aroui, M. Garrido & S. Girard. "Quasi-conjugate bayes estimates for GPD parameters and application to heavy tails modelling", Extremes, 8, 57-78, 2005.

[31] L. Gardes & S. Girard. "Asymptotic distribution of a Pickands-type estimator of the extreme value index", Comptes-Rendus de l'Académie des Sciences, t. 341, Série I, 53-58, 2005.

[30] L. Gardes & S. Girard. "Estimating extreme quantiles of Weibull tail-distributions", Communication in Statistics - Theory and Methods, 34, 1065-1080, 2005.

[29] C. Amblard & S. Girard. "Estimation procedures for a semiparametric family of bivariate copulas", Journal of Computational and Graphical Statistics, 14(2), 1-15, 2005.

[28] S. Girard & S. Iovleff. "Auto-Associative Models and Generalized Principal Component Analysis", Journal of Multivariate Analysis, 93(1), 21-39, 2005.

[27] S. Girard, A. Iouditski & A. Nazin. "L1-optimal frontier estimation via linear programming", Automation and Remote Control, 66(12), 2000-2018, 2005.

[26] S. Girard & L. Menneteau. "Central limit theorems for smoothed extreme value estimates of point processes boundaries", Journal of Statistical Planning and Inference, 135(2), 433-460, 2005.

[25] S. Girard & P. Jacob. "Asymptotic normality of the L1-error for Geffroy's estimate of point process boundaries", Publications de l'Institut de Statistique de l'Université de Paris, XLIX, 3-17, 2005.

[24] G. Bouchard, S. Girard, A. Iouditski & A. Nazin. "Some linear programming methods for frontier estimation", Applied Stochastic Models in Business and Industry, 21(2), 175-185, 2005.

[23] A. Gannoun, S. Girard, C. Guinot & J. Saracco. "Sliced Inverse Regression in reference curves estimation", Computational Statistics and Data Analysis , 46(3), 103-122, 2004.

[22] A. Gannoun, S. Girard, C. Guinot & J. Saracco. "Implémentation en C d'estimateurs non- paramétriques de quantiles conditionnels. Application au tracé de courbes de référence", La revue de Modulad, 31, 59-70, 2004.

[21] S. Girard & P. Jacob. "Extreme values and kernel estimates of point processes boundaries", ESAIM: Probability and Statistics, 8, 150-168, 2004.

[20] S. Girard. "On the asymptotic normality of the L1 error for Haar series estimates of Poisson point processes boundaries", Statistics and Probability Letters, 66, 81-90, 2004.

[19] G. Bouchard, S. Girard, A. Iouditski & A. Nazin. "Nonparametric estimation of the support boundary through linear programming", Automation and Remote Control, 65(1), 58-64, 2004.

[18] S. Girard. "A Hill type estimate of the Weibull tail-coefficient", Communication in Statistics - Theory and Methods , 33(2), 205-234, 2004.

[17] S. Girard & P. Jacob. "Projection estimates of point processes boundaries", Journal of Statistical Planning and Inference, 116(1), 1-15, 2003.

[16] S. Girard & P. Jacob. "Extreme value and Haar series estimates of point process boundaries", Scandinavian Journal of Statistics, 30(2), 369-384, 2003.

[15] J. Diebolt, M. Garrido & S. Girard "Asymptotic normality of the ET method for extreme quantile estimation. Application to the ET test", Comptes-Rendus de l'Académie des Sciences, t. 337, Série I, 213-218, 2003.

[14] J. Diebolt, J. Ecarnot, M. Garrido, S. Girard & D. Lagrange. "Le logiciel Extremes, un outil pour l'étude des queues de distribution", La revue de Modulad, 30, 53-60, 2003.

[13] J. Diebolt & S. Girard. "A Note on the asymptotic normality of the ET method for extreme quantile estimation", Statistics and Probability Letters, 62(4), 397-406, 2003.

[12] C. Amblard & S. Girard. "Symmetry and dependence properties within a semiparametric family of bivariate copulas", Nonparametric Statistics, 14(6), 715-727, 2002.

[11] A. Gannoun, S. Girard, C. Guinot & J. Saracco. "Reference ranges based on nonparametric quantile regression", Statistics in Medicine, 21(20), 3119-3135, 2002.

[10] A. Gannoun, S. Girard, C. Guinot & J. Saracco. "Trois méthodes non paramétriques pour l'estimation de courbes de référence - Application l'analyse de propriétés biophysiques de la peau", Revue de Statistique Appliquée, L(1), 65-89, 2002.

[9] C. Amblard & S. Girard. "A semiparametric family of symmetric bivariate copulas", Comptes-Rendus de l'Académie des Sciences, t. 333, Série I, 129-132, 2001.

[8] S. Girard. "A nonlinear PCA based on manifold approximation", Computational Statistics, 15(2), 145-167, 2000.

[7] B. Chalmond & S. Girard. "Nonlinear modeling of scattered multivariate data and its application to shape change", IEEE Pattern Analysis and Machine Intelligence, 21(5), 422-432, 1999.

[6] S. Girard & J. Diebolt. "Consistency of the ET method and smooth variations", Comptes-Rendus de l'Académie des Sciences, t. 329, Série I, 821-826, 1999.

[5] S. Girard, B. Chalmond & J-M. Dinten. "Position of principal component analysis among auto-associative composite models", Comptes-Rendus de l'Académie des Sciences, t. 326, Série I, 763-768, 1998.

[4] S. Girard, B. Chalmond & J-M. Dinten. "Une ACP non-linéaire basée sur l'approximation par variétés", Revue de Statistique Appliquée, XLVI(3), 5-19, 1998.

[3] S. Girard, P. Guérin, H. Maître & M. Roux. "Building detection from high resolution colour images", In Image and Signal Processing for Remote Sensing, S.B. Serpico (ed.), vol. 3500, p. 278-289, SPIE, 1998.

[2] S. Girard, B. Chalmond & J-M. Dinten. "Designing non linear models for flexible curves",  In Curves and Surfaces with Application in CAGD, A. Le Méhauté, C. Rabut, and L.L. Schumaker (eds.), 135-142, 1997.

[1] S. Girard, J-M. Dinten & B. Chalmond. "Building and training radiographic flexible prior models for object identification from incomplete data", IEE proceedings on Vision, Image and Signal Processing, 143(4), 257-264, 1996.