[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,
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radiographic flexible prior models for object identification from incomplete data", IEE proceedings on Vision, Image and Signal Processing, 143(4), 257-264, 1996. |