Bibliography

• 1C. Amblard, S. Girard.
  
  Estimation procedures for a semiparametric family of bivariate copulas, in: Journal of Computational and Graphical Statistics, 2005, vol. 14, n^o 2, p. 1–15.
• 2J. Blanchet, F. Forbes.
  
  Triplet Markov fields for the supervised classification of complex structure data, in: IEEE trans. on Pattern Analyis and Machine Intelligence, 2008, vol. 30(6), p. 1055–1067.
• 3C. Bouveyron, S. Girard, C. Schmid.
  
  High dimensional data clustering, in: Computational Statistics and Data Analysis, 2007, vol. 52, p. 502–519.
• 4C. Bouveyron, S. Girard, C. Schmid.
  
  High dimensional discriminant analysis, in: Communication in Statistics - Theory and Methods, 2007, vol. 36, n^o 14.
• 5G. Celeux, S. Chrétien, F. Forbes, A. Mkhadri.
  
  A Component-wise EM Algorithm for Mixtures, in: Journal of Computational and Graphical Statistics, 2001, vol. 10, p. 699–712.
• 6G. Celeux, F. Forbes, N. Peyrard.
  
  EM procedures using mean field-like approximations for Markov model-based image segmentation, in: Pattern Recognition, 2003, vol. 36, n^o 1, p. 131-144.
• 7F. Forbes, G. Fort.
  
  Combining Monte Carlo and Mean field like methods for inference in hidden Markov Random Fields, in: IEEE trans. PAMI, 2007, vol. 16, n^o 3, p. 824-837.
• 8F. Forbes, N. Peyrard.
  
  Hidden Markov Random Field Model Selection Criteria based on Mean Field-like Approximations, in: IEEE trans. PAMI, August 2003, vol. 25(9), p. 1089–1101.
• 9S. Girard.
  
  A Hill type estimate of the Weibull tail-coefficient, in: Communication in Statistics - Theory and Methods, 2004, vol. 33, n^o 2, p. 205–234.
• 10S. Girard, P. Jacob.
  
  Extreme values and Haar series estimates of point process boundaries, in: Scandinavian Journal of Statistics, 2003, vol. 30, n^o 2, p. 369–384.

Articles in International Peer-Reviewed Journals

• 11L. Bergé, C. Bouveyron, S. Girard.
  
  HDclassif: an R Package for Model-Based Clustering and Discriminant Analysis of High-Dimensional Data, in: Journal of Statistical Software, 2012, vol. 46, n^o 6, p. 1–29.
  
  http://hal.inria.fr/hal-00541203
• 12J. Carreau, D. Ceresetti, E. Ursu, S. Anquetin, J. Creutin, L. Gardes, S. Girard, G. Molinié.
  
  Evaluation of classical spatial-analysis schemes of extreme rainfall, in: Natural Hazards and Earth System Sciences, 2012, vol. 12, p. 3229–3240.
• 13L. Chaari, T. Vincent, F. Forbes, M. Dojat, P. Ciuciu.
  
  Fast joint detection-estimation of evoked brain activity in event-related fMRI using a variational approach., in: IEEE Transactions on Medical Imaging, October 2012. [ DOI : 10.1109/TMI.2012.2225636 ]
  
  http://hal.inria.fr/inserm-00753873
• 14M. Charras-Garrido, L. Azizi, F. Forbes, S. Doyle, N. Peyrard, D. Abrial.
  
  On the difficulty to clearly identify and delineate disease risk hot spots, in: International Journal of Applied Earth Observation and Geoinformation, May 2012, available on line.
• 15A. Daouia, L. Gardes, S. Girard.
  
  On kernel smoothing for extremal quantile regression, in: Bernoulli, 2013, to appear.
• 16J. Durand, S. Girard, V. Ciriza, L. Donini.
  
  Optimization of power consumption and user impact based on point process modeling of the request sequence, in: Journal of the Royal Statistical Society series C, 2013, to appear.
• 17J. El Methni, L. Gardes, S. Girard, A. Guillou.
  
  Estimation of extreme quantiles from heavy and light tailed distributions, in: Journal of Statistical Planning and Inference, 2012, vol. 142, n^o 10, p. 2735-2747.
  
  http://hal.inria.fr/hal-00627964
• 18L. Gardes, S. Girard.
  
  Functional kernel estimators of large conditional quantiles, in: Electronic Journal of Statistics, 2012, vol. 6, p. 1715-1744.
  
  http://hal.inria.fr/hal-00608192
• 19S. Girard, A. Guillou, G. Stupfler.
  
  Estimating an endpoint with high order moments in the Weibull domain of attraction, in: Statistics and Probability Letters, December 2012, vol. 82, p. 2136-2144.
  
  http://hal.inria.fr/hal-00648435
• 20S. Girard, A. Guillou, G. Stupfler.
  
  Estimating an endpoint with high order moments, in: Test, 2012, vol. 21, n^o 4, p. 697–729.
  
  http://hal.inria.fr/inria-00596979
• 21S. Girard, A. Guillou, G. Stupfler.
  
  Frontier estimation with kernel regression on high order moments, in: Journal of Multivariate Analysis, 2013, vol. 116, p. 172–189.
• 22C. Hatt, F. Mankessi, J.-B. Durand, F. Boudon, F. Montes, M. Lartaud, J.-L. Verdeil, O. Monteeuis.
  
  Characteristics of Acacia mangium shoot apical meristems in natural and in vitro conditions in relation to heteroblasty, in: Trees - Structure and Function, 2012, vol. 26, n^o 3, p. 1031-1044, PDF version of the authors can be published in January 2013. [ DOI : 10.1007/s00468-012-0680-0 ]
  
  http://hal.inria.fr/hal-00699815
• 23S. 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, in: Journal of Low Power Electronics, 2012, vol. 8, p. 113–124.

International Conferences with Proceedings

• 24C. Amblard, S. Girard, L. Menneteau.
  
  Algebraic properties of copulas defined from matrices, in: Workshop on Copulae in Mathematical and Quantitative Finance, Cracovie, Pologne, juillet 2012.
• 25C. Bakhous, F. Forbes, T. Vincent, L. Chaari, M. Dojat, P. Ciuciu.
  
  Adaptive experimental condition selection in event-related fMRI, in: ISBI 2012 - IEEE International Symposium on Biomedical Imaging, Barcelone, Spain, IEEE, May 2012, p. 1755-1758. [ DOI : 10.1109/ISBI.2012.6235920 ]
  
  http://hal.inria.fr/cea-00710489
• 26C. Bakhous, F. Forbes, T. Vincent, M. Dojat, P. Ciuciu.
  
  Variational variable selection to assess experimental condition relevance in event-related fMRI, in: ISBI 2013 - IEEE International Symposium on Biomedical Imaging, San Francisco, USA, IEEE, May 2013.
• 27C. Bouveyron, M. Fauvel, S. Girard.
  
  Kernel discriminant analysis and clustering with parsimonious Gaussian process models, in: ICML workshop on Object, functional and structured data : towards next generation kernel-based methods, Edinburgh, United Kingdom, 2012.
  
  http://hal.inria.fr/hal-00707056
• 28L. Chaari, F. Forbes, T. Vincent, P. Ciuciu.
  
  Hemodynamic-informed parcellation of fMRI data in a Joint Detection Estimation framework, in: International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Nice, France, October 1-5 2012.
• 29L. Chaari, F. Forbes, T. Vincent, P. Ciuciu.
  
  Robust voxel-wise Joint Detection Estimation of brain activity in fMRI, in: IEEE International Conference on Image Processing (ICIP), Orlando, USA, September 30-October 3 2012.
• 30A. Daouia, L. Gardes, S. Girard.
  
  On kernel smoothing for extremal quantile regression, in: 5th International Conference of the ERCIM WG on computing and statistics, Oviedo, Spain, décembre 2012.
• 31S. Joshi, A. Lombardot, M. Belleville, E. Beigne, S. Girard.
  
  Statistical leakage estimation in 32nm CMOS considering cells correlations, in: 11th IEEE conference on Faible Tension Faible Consommation, Paris, juin 2012.
• 32G. Mazo, F. Forbes, S. Girard.
  
  Augmented cumulative distribution networks for multivariate extreme value modelling, in: 5th International Conference of the ERCIM WG on Computing and Statistics, Oviedo, Spain, December 2012.
• 33K. Qin, F. Raimondo, F. Forbes, Y. S. Ong.
  
  An Improved CUDA-Based Implementation of Differential Evolution on GPU, in: Genetic and Evolutionary Computation Conference 2012 (Gecco 2012), July 12-16 2012.

National Conferences with Proceeding

• 34C. Bakhous, F. Forbes, T. Vincent, L. Chaari, M. Dojat, P. Ciuciu.
  
  Sélection de variable dans un cadre bayésien de traitement de données d'IRM fonctionnelle, in: Journées de Statistique de la Société Française de Statistique (SFdS), Brussels, Belgium, May 21-25 2012.
• 35C. Bouveyron, M. Fauvel, S. Girard.
  
  Processus gaussiens parcimonieux pour la classification générative de données hétérogènes, in: 44èmes Journées de Statistique de la Société Française de Statistique, Bruxelles, Belgium, 2012.
  
  http://hal.inria.fr/hal-00707059
• 36L. Chaari, F. Forbes, P. Ciuciu, T. Vincent.
  
  Parcel-free Joint Detection-Estimation in fMRI, in: Journées de Statistique de la Société Française de Statistique (SFdS), Brussels, Belgium, May 21-25 2012.
• 37J. El-Methni, L. Gardes, S. Girard.
  
  Estimation de l'espérance conditionnelle des pertes extrêmes dans le cas de lois à queues lourdes en présence d'une covariable, in: 44èmes Journées de Statistique organisées par la Société Française de Statistique, Bruxelles, Belgique, mai 2012.
• 38S. Girard, A. Guillou, G. Stupfler.
  
  Estimation de point terminal dans le domaine d'attraction de Weibull par une méthode des moments d'ordre élevé, in: 44èmes Journées de Statistique organisées par la Société Française de Statistique, Bruxelles, Belgique, mai 2012.
• 39J. Saracco, M. Chavent, B. Liquet, V. Kuentz, T. Nguyen, S. Girard.
  
  Régression inverse par tranches sur flux de données, in: 44èmes Journées de Statistique organisées par la Société Française de Statistique, Bruxelles, Belgique, mai 2012.

Conferences without Proceedings

• 40L. Bergé, C. Bouveyron, S. Girard.
  
  HDclassif: An R Package for Model-Based Clustering and Discriminant Analysis of High-Dimensional Data, in: 1ères Rencontres R, Bordeaux, France, July 2012.
  
  http://hal.inria.fr/hal-00717506
• 41L. Gardes, S. Girard.
  
  Functional kernel estimators of conditional extreme quantiles, in: 7èmes Journées de Statistique Fonctionnelle et Opératorielle, Montpellier, juin 2012.

Scientific Books (or Scientific Book chapters)

• 42A. Daouia, L. Gardes, S. Girard.
  
  Nadaraya's estimates for large quantiles and free disposal support curves, in: Exploring research frontiers in contemporary statistics and econometrics, I. V. Keilegom, P. Wilson (editors), Springer, 2012, p. 1-22.
  
  http://hal.inria.fr/hal-00528670

Internal Reports

• 43J.-B. Durand, Y. Guédon.
  
  Localizing the Latent Structure Canonical Uncertainty: Entropy Profiles for Hidden Markov Models, Inria, February 2012, n^o RR-7896, 43 p, Submitted to Journal of Machine Learning Research.
  
  http://hal.inria.fr/hal-00675223
• 44V. Khalidov, F. Forbes, R. Horaud.
  
  Calibration of A Binocular-Binaural Sensor Using a Moving Audio-Visual Target, Inria, January 2012, n^o RR-7865, 27 p.
  
  http://hal.inria.fr/hal-00662306

Other Publications

• 45C. Bouveyron, M. Fauvel, S. Girard.
  
  Kernel discriminant analysis and clustering with parsimonious Gaussian process models.
  
  http://hal.inria.fr/hal-00687304
• 46M. Chavent, S. Girard, V. Kuentz, B. Liquet, T. M. N. Nguyen, J. Saracco.
  
  A sliced inverse regression approach for data stream.
  
  http://hal.inria.fr/hal-00688609
• 47R. Coudret, S. Girard, J. Saracco.
  
  A new sliced inverse regression method for multivariate response regression.
  
  http://hal.inria.fr/hal-00714981
• 48A. Daouia, S. Girard, A. Guillou.
  
  A Gamma-moment approach to monotonic boundaries estimation: with applications in econometric and nuclear fields.
  
  http://hal.inria.fr/hal-00737732
• 49E. Deme, L. Gardes, S. Girard.
  
  On the estimation of the second order parameter for heavy-tailed distributions, 2012.
  
  http://hal.inria.fr/hal-00634573/fr/
• 50E. H. Deme, S. Girard, A. Guillou.
  
  Reduced-bias estimator of the Proportional Hazard Premium for heavy-tailed distributions, 2012.
  
  http://hal.inria.fr/hal-00763978
• 51S. Girard, A. Guillou, G. Stupfler.
  
  Uniform strong consistency of a frontier estimator using kernel regression on high order moments.
  
  http://hal.inria.fr/hal-00764425

• 52C. Biernacki, G. Celeux, G. Govaert, F. Langrognet.
  
  Model-Based Cluster and Discriminant Analysis with the MIXMOD Software, in: Computational Statistics and Data Analysis, 2006, vol. 51, n^o 2, p. 587–600.
• 53C. Bouveyron.
  
  Modélisation et classification des données de grande dimension. Application à l'analyse d'images, Université Grenoble 1, septembre 2006.
  
  http://tel.archives-ouvertes.fr/tel-00109047
• 54C. Bouveyron, S. Girard, C. Schmid.
  
  High-dimensional data clustering, in: Computational Statistics & Data Analysis, 2007, vol. 52, n^o 1, p. 502–519.
• 55M. Charras-Garrido.
  
  Modélisation des événements rares et estimation des quantiles extrêmes, méthodes de sélection de modèles pour les queues de distribution, Université Grenoble 1, juin 2002.
  
  http://mistis.inrialpes.fr/people/girard/Fichiers/theseGarrido.pdf
• 56C. Chen, F. Forbes, O. Francois.
  
  FASTRUCT: Model-based clustering made faster, in: Molecular Ecology Notes, 2006, vol. 6, p. 980–983.
• 57G. Dewaele, F. Devernay, R. Horaud, F. Forbes.
  
  The alignment between 3D-data and articulated shapes with bending surfaces, in: European Conf. Computer Vision, Lecture notes in Computer Science, 2006, n^o 3, p. 578-591.
• 58P. Embrechts, C. Klüppelberg, T. Mikosh.
  
  Modelling Extremal Events, Applications of Mathematics, Springer-Verlag, 1997, vol. 33.
• 59F. Ferraty, P. Vieu.
  
  Nonparametric Functional Data Analysis: Theory and Practice, Springer Series in Statistics, Springer, 2006.
• 60O. Francois, S. Ancelet, G. Guillot.
  
  Bayesian clustering using Hidden Markov Random Fields in spatial genetics, in: Genetics, 2006, p. 805–816.
• 61A. E. Gelfand, A. M. Schmidt, S. Banerjee, C. Sirmans.
  
  Nonstationary multivariate process modeling through spatially varying coregionalization, in: Test, 2004, vol. 13, p. 263-312.
  
  http://dx.doi.org/10.1007/BF02595775
• 62S. Girard.
  
  Construction et apprentissage statistique de modèles auto-associatifs non-linéaires. Application à l'identification d'objets déformables en radiographie. Modélisation et classification, Université de Cery-Pontoise, octobre 1996.
• 63Y. Goegebeur, J. Beirlant, T. de Wet.
  
  Kernel estimators for the second order parameter in extreme value statistics, in: Journal of Statistical Planning and Inference, 2010, vol. 140, n^o 9, p. 2632–2652.
• 64M. Gomes, L. de Haan, L. Peng.
  
  Semi-parametric Estimation of the Second Order Parameter in Statistics of Extremes, in: Extremes, 2002, vol. 5, n^o 4, p. 387–414.
• 65R. Horaud, F. Forbes, M. Yguel, G. Dewaele, J. Zhang.
  
  Rigid and Articulated Point Registration with Expectation Conditional Maximization, in: IEEE Transactions on Pattern Analysis and Machine Intelligence, March 2011, vol. 33, n^o 3, p. 587–602. [ DOI : 10.1109/TPAMI.2010.94 ]
  
  http://hal.inria.fr/inria-00590265/en
• 66M. Jones.
  
  A dependent bivariate t distribution with marginals on different degrees of freedom, in: Statistics and Probability Letters, 2002, vol. 56, n^o 2, p. 163-170.
• 67S. Kotz, S. Nadarajah.
  
  Multivariate t Distributions and their Applications, Cambridge, 2004.
• 68K. Li.
  
  Sliced inverse regression for dimension reduction, in: Journal of the American Statistical Association, 1991, vol. 86, p. 316–327.
• 69R. Nelsen.
  
  An introduction to copulas, Lecture Notes in Statistics, Springer-Verlag, New-York, 1999, vol. 139.
• 70J. Pritchard, M. Stephens, P. Donnelly.
  
  Inference of Population Structure Using Multilocus Genotype Data, in: Genetics, 2000, vol. 155, p. 945–959.
• 71H. Rue, S. Martino, N. Chopin.
  
  Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations (with discussion), in: Journal of the Royal Statistical Society B, 2009, vol. 71, p. 319–392.
• 72A. M. Schmidt, M. A. Rodriguez.
  
  Modelling multivariate counts varying continuously in space, in: Bayesian Statistics, J. M. Bernardo, M. J. Bayarri, J. O. Berger, A. P. Dawid, D. Heckerman, A. F. M. Smith, M. West (editors), Oxford University Press, 2010.
• 73W. T. Shaw, K. T. A. Lee.
  
  Bivariate Student distributions with variable marginal degrees of freedom and independence, in: Journal of Multivariate Analysis, 2008, vol. 99, n^o 6, p. 1276-1287.
• 74P. Taberlet, E. Coissac, M. Hajibabaei, L. Rieseberg.
  
  Environmental DNA, 2011, vol. 21, Molecular Ecology, special issue.
• 75M. Vignes, J. Blanchet, D. Leroux, F. Forbes.
  
  SpaCEM3, a software for biological module detection when data is incomplete, high dimensional and dependent, in: Bioinformatics, 2011, vol. 27, n^o 6, p. 881-882.