PhD theseshere 
M. Allouche,
"Contributions to generative modeling and dictionary learning: Theory and application", Institut Polytechnique de Paris, décembre 2022
[pdf].

A. Constantin,
"Analyse de séries temporelles massives d'images satellitaires: Applications à la cartographie des écosystèmes", Université Grenoble Alpes, décembre 2021
[pdf].

M. Lopes,
"Suivi écologique des prairies seminaturelles : analyse statistique de séries temporelles denses d'images satellite à haute résolution spatiale", Université de Toulouse, novembre 2017
[pdf].

S. N. Sylla, "Modélisation et classification de données binaires en grande dimension  Application à l'autopsie verbale", Université Gaston Berger, Sénégal, décembre 2016
[pdf].

A. Chiancone, "Réduction de dimension via Sliced Inverse Regression: Idées et nouvelles propositions", Université Grenoble Alpes, octobre 2016
[pdf].

G. Mazo,
"Construction et estimation de copules en grande dimension", Université Grenoble 1, novembre 2014
[pdf].

C. Bouveyron, "Modélisation
et classification des données de grande dimension. Application à l'analyse d'images", Université Grenoble 1,
septembre 2006 [pdf]. 
Classification of highdimensional data 
A. Constantin, M. Fauvel & S. Girard,
"Mixture of multivariate Gaussian processes for classification of irregularly sampled satellite image timeseries", Statistics and Computing, 32, 79, 2022.
[Associated technical report: pdf]. 
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, 113, 2022.
[Associated technical report: pdf]. 
M. Lopes, M. Fauvel, A. Ouin & S. Girard.
"Spectrotemporal heterogeneity measures from dense high spatial resolution satellite image time series: Application to grassland species diversity estimation", Remote Sensing, 9 (10), 2017.
[Associated technical report: pdf]. 
M. Lopes, M. Fauvel, S. Girard & D. Sheeren.
"Objectbased classification from high resolution satellite image time series with Gaussian mean map kernels: Application to grassland management practices", Remote Sensing, 9 (7), 2017.
[Associated technical report: pdf]. 
S. Girard and J. Saracco. "Supervised and unsupervised classification using mixture models" In D. FraixBurnet and S. Girard, editors, Statistics for astrophysics, clustering and classification, volume 77, pages 6990, EDP Sciences, 2016.
[Associated technical report: pdf]. 
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, 240255, 2015.
[Associated technical report: pdf]. 
M. Fauvel, C. Bouveyron and S. Girard, "Parsimonious Gaussian process models for the classification of hyperspectral remote sensing images", IEEE Geoscience and Remote Sensing Letters, 12, 24232427, 2015.
[Associated technical report: pdf]. 
C. Bouveyron, M. Fauvel & S. Girard.
"Kernel discriminant analysis and clustering with parsimonious Gaussian process models",
Statistics and Computing, 25, 11431162, 2015.
[Associated technical report: pdf].

L. Bergé, C. Bouveyron & S. Girard. "HDclassif: An R package for modelbased clustering and discriminant analysis of highdimensional data, Journal of Statistical Software, 46(6), 129, 2012.
[Associated technical report: pdf].

C. Bouveyron & S. Girard. "Robust supervised classification with mixture models: Learning from data with uncertain labels",
Pattern Recognition, 42(11), 26492658, 2009.
[Associated technical report: pdf].


C. Bouveyron & S. Girard. "Classification supervisée et non supervisée des données de grande dimension, La revue Modulad, 40, 81102, 2009.

C. Bouveyron, S. Girard & C. Schmid. "Highdimensional discriminant
Analysis", Communication in Statistics  Theory and Methods,
36(14), 26072623, 2007.
[Associated technical report (in french):
ps/pdf]. 

C. Bouveyron, S. Girard & C. Schmid. "High Dimensional Data Clustering", Computational Statistics and Data Analysis, 52, 502519, 2007.
[Associated technical report: ps/pdf]. 

C. Bouveyron, S. Girard & C. Schmid. "Classspecific subspace
discriminant analysis for highdimensional data", In C. Saunders et
al., editors, Lecture Notes in Computer Science, volume 3940,
p. 139150. SpringerVerlag, Berlin Heidelberg, 2006. 

Dimension reduction with nonlinear
Principal Component Analysis 
S. Girard & S. Iovleff. "Autoassociative 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. 205222, LNCSE, SpringerVerlag, 2007.
[Associated technical report:
ps/pdf].

S. Girard & S. Iovleff. "AutoAssociative Models and Generalized
Principal Component Analysis", Journal of Multivariate Analysis,
93(1):2139, 2005.
[Associated technical report:
ps/pdf]. 

S. Girard."A nonlinear PCA based on manifold approximation", Computational Statistics, 15(2):145167, 2000.
[Associated technical report:
pdf]. 

B. Chalmond & S. Girard. "Nonlinear modeling of scattered
multivariate data and its application to shape change", IEEE Pattern Analysis
and Machine Intelligence, 21(5):422432, 1999.
[Associated technical report: pdf]. 

S. Girard, B. Chalmond & JM. Dinten. "Position of principal
component analysis among autoassociative composite models", ComptesRendus
de l'Académie des Sciences, t. 326, Série I:763768,
1998. 

S. Girard, B. Chalmond & JM. Dinten. "Une ACP nonlinéaire
basée sur l'approximation par variétés", Revue
de Statistique Appliquée, XLVI(3):519, 1998. 

S. Girard, B. Chalmond & JM. Dinten. "Designing non linear models
for flexible curves", Curves and Surfaces with Application in
CAGD, A. Le Méhauté, C. Rabut, and L.L. Schumaker
(eds.), 135142, 1997. 
See also Applications of statistics.

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

S. Girard.
"Transformation of a copula using the associated cocopula",
Dependence Modeling, 6, 298308, 2018.
[associated technical report: pdf].

F. Durante, S. Girard & G. Mazo.
"MarshallOlkin type copulas generated by a global shock",
Journal of Computational and Applied Mathematics, 296, 638648, 2016.
[associated technical report: pdf].

G. Mazo, S. Girard & F. Forbes.
"A flexible and tractable class of onefactor copulas",
Statistics and Computing, 26, 965979, 2016.
[associated technical report: pdf].

G. Mazo, S. Girard & F. Forbes.
"A class of multivariate copulas based on products of bivariate copulas", Journal of Multivariate Analysis, 140, 363376, 2015.
[associated technical report: pdf].

G. Mazo, S. Girard & F. Forbes.
"Weighted least square inference based on dependence coefficients for multivariate copulas",
ESAIM: Probability and Statistics, 19, 746765, 2015.
[associated technical report: pdf].

L. Gardes & S. Girard. "Nonparametric estimation of the conditional tail copula", Journal of Multivariate Analysis, 137, 116, 2015.
[associated technical report: pdf].

F. Durante, S. Girard & G. Mazo.
"Copulas based on MarshallOlkin machinery", In U. Cherubini et al, editors,
MarshallOlkin Distributions. Advances in Theory and Applications, volume 141 of Springer Proceedings in Mathematics and Statistics, pages 1531, Springer, 2015.
[Associated technical report: pdf].

C. Amblard & S. Girard.
"A new bivariate extension of FGM copulas", Metrika, 70, 117, 2009.
[Associated technical report: pdf].

C. Amblard & S. Girard. "Estimation procedures for a
semiparametric family of bivariate copulas", Journal of
Computational and Graphical Statistics, 14(2), 115, 2005.
[Associated technical report: pdf
ps]. 

C. Amblard & S. Girard. "Symmetry and dependence properties
within a semiparametric family of bivariate copulas", Nonparametric
Statistics, 14(6), 715727, 2002.
[Associated technical report: pdf
]. 

C. Amblard & S. Girard. "A semiparametric family of symmetric
bivariate copulas", ComptesRendus de l'Académie des
Sciences, t. 333,Série I:129132, 2001. 

Intrinsic dimension estimation 
O. Chelly, L. Amsaleg, T. Furon, S. Girard, M. Houle, K. Kawarabayashi & M. Nett.
"ExtremeValueTheoretic Estimation of Local Intrinsic Dimensionality",
Journal of Data Mining and Knowledge Discovery,
32 (6), 17681805, 2018.
[Associated technical report: pdf].

C. Bouveyron, G. Celeux & S. Girard. "Intrinsic dimension estimation by maximum likelihood in isotropic probabilistic PCA",
Pattern Recognition Letters, 32(14), 17061713, 2011.
[Associated technical report: pdf].

Dimension reduction in regression 
M. Bousebata, G. Enjolras & S. Girard,
"Extreme Partial LeastSquares", Journal of Multivariate Analysis, to appear, 2022.
[Associated technical report: pdf],
[Code: github].

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

A. Chiancone, F. Forbes & S. Girard.
"Student Sliced Inverse Regression",
Computational Statistics and Data Analysis, 113, 441456, 2017.
[Associated technical report: pdf].

A. Chiancone, S. Girard & J. Chanussot.
"Collaborative Sliced Inverse Regression",
Communications in Statistics  Theory and Methods,
46, 60356053, 2017.
[Associated technical report: pdf].

S. Girard & J. Saracco. "An introduction to dimension reduction in nonparametric kernel regression" In D. FraixBurnet and D. VallsGabaud, editors, Regression methods for astrophysics, volume 66, pages 167196, EDP Sciences, 2014.
[Associated technical report: pdf],
[Data and code: tar.gz]. 
R. Coudret, S. Girard, & J. Saracco.
"A new sliced inverse regression method for multivariate response",
Computational Statistics and Data Analysis, 77, 285299, 2014.
[Associated technical report: pdf]. 
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, 11291152, 2014.
[Associated technical report: pdf]. 
C. BernardMichel, 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.
[Associated technical report:
pdf]. 
C. BernardMichel, L. Gardes & S. Girard. "A Note on Sliced Inverse Regression with Regularizations", Biometrics, 64, 982986, 2008. [Associated technical report: pdf]. 
C. BernardMichel, L. Gardes & S. Girard.
"Gaussian Regularized Sliced Inverse Regression", Statistics and Computing, 19, 8598, 2009.
[Associated technical report: pdf].

A. Gannoun, S. Girard, C. Guinot & J. Saracco. "Sliced
Inverse Regression in reference curves estimation", Computational Statistics and Data Analysis , 46(3):103122, 2004.
[Associated technical report: pdf ps]. 

A. Gannoun, S. Girard, C. Guinot & J. Saracco. "Reference ranges based on nonparametric quantile regression", Statistics in Medicine, 21(20):31193135, 2002. 
Bayesian approaches 
T. Moins, J. Arbel, A. Dutfoy & S. Girard,
"On the use of a local Rhat to improve MCMC convergence",
Bayesian Analysis, to appear,
[Associated technical report: pdf, code: github]. 

T. Moins, J. Arbel, A. Dutfoy & S. Girard,
"Discussion of the paper 'RankNormalization, Folding, and Localization: An Improved Rhat for Assessing Convergence of MCMC'", Bayesian Analysis, 16(2), 711712, 2021.
[Associated technical report: pdf]. 
