Classification supervisée en grande dimension. Application à l'agrément de conduite automobile
Revue de Statistique Appliquée, Volume 54 (2006) no. 4, p. 41-60
@article{RSA_2006__54_4_41_0,
     author = {Poggi, Jean-Michel and Tuleau, Christine},
     title = {Classification supervis\'ee en grande dimension. Application \`a l'agr\'ement de conduite automobile},
     journal = {Revue de Statistique Appliqu\'ee},
     publisher = {Soci\'et\'e fran\c caise de statistique},
     volume = {54},
     number = {4},
     year = {2006},
     pages = {41-60},
     language = {fr},
     url = {http://www.numdam.org/item/RSA_2006__54_4_41_0}
}
Classification supervisée en grande dimension. Application à l'agrément de conduite automobile. Revue de Statistique Appliquée, Volume 54 (2006) no. 4, pp. 41-60. http://www.numdam.org/item/RSA_2006__54_4_41_0/

[1] Amato U., Antoniadis A.and De Feis I. ( 2005), Dimension reduction in functional regression with applicarions, To appear in Comp. Stat. and Data. Anal. | Zbl pre05381685

[2] Ansaldi N. ( 2002), Contributions des méthodes statistiques à la quantification de l'agrément de conduite, PhD thesis, Marne-la-Vallée.

[3] Barron A.R., Birgé L. and Massart P. ( 1999), Risk bounds for model selection via penalization, Probability Theory and Related Fieds, 113 :301-413. | MR 1679028 | Zbl 0946.62036

[4] Besse P. and Cardot H. ( 2003), Modélisation statistique de données fonctionnelles, in G. Covaert, editor, Analyse de données, Hermes.

[5] Biau G., Bunea F.and Wegkamp M. ( 2005), Functional classification in Hilbert spaces, IEEE Trans. inf. Theory, 51(6) :2163-2172. | MR 2235289

[6] Bigot J. ( 2003), Recalage des signaux et analyse de la variance fonctionnelle par ondelettes; application au domaine biomédical, PhD thesis, Grenoble.

[7] Breiman L., Friedman J., Olshen R.and Stone C. ( 1984), Classification and Regression Trees, Chapman et Hall. | MR 726392 | Zbl 0541.62042

[8] Coifman R.and Saito N. ( 1964), Constructions of local orthonormal bases for classification and regression, C. R. Acad. Sci. Paris (Ser. 1) : 191-196. | Zbl 0801.62004

[9] Coifman R.and Wickerhauser M. ( 1992), Entropy-based algorithms for best basis selection, IEEE Trans. Inform. Theory, 38(2) :713-719. | Zbl 0849.94005

[10] Dauxois J. and Pousse A. ( 1976), Les analyses factorielles en calcul des probabilités et en statistique : essai d'étude synthétique, PhD thesis, université Toulouse III.

[11] Deville J.C. ( 1974), Méthodes statistiques et numériques de l'analyse harmonique, Annales de l'Insee, 15 :7-97.

[12] Donoho D. and Johnstone I. ( 1994), Ideal spatial adaptation by wavelet shrinkage, Biometrika, 81(3) :425-455. | MR 1311089 | Zbl 0815.62019

[13] Dudoit S., Fridlyand J. and Speed T. ( 2002), Comparison of discrimination methods for the classification of tumors using gene expression data, Journal of the American Statistical Association, 97(457) :77-87. | MR 1963389 | Zbl 1073.62576

[14] Favre C. ( 1999), Analyse en normes L1 et L° des distances et des préférences. Planification en analyse sensorielle. Application au confort d'accueil de sièges automobiles, PhD thesis, Université de Rennes II.

[15] Ferraty F. and Vieu P. ( 2003), Curves discrimination : a nonparametric functional approach, Computational Statistics and Data Analysis, 44(1-2) :161-173. | MR 2020144 | Zbl pre05373903

[16] Ferré L. and Villa N. ( 2005), Discrimination de courbes par régression inverse fonctionnelle, Revue de Statistique Appliquée, LIII(l) :39-57. | Numdam

[17] Ferré L. and Yao A.F. ( 2003) Functional sliced inverse regression analysis, Statistics, 37(6) :475-488. | MR 2022235 | Zbl 1032.62052

[18] Ghattas B. ( 1999), Agrégation d'arbres de classification, Revue de Statistique Appliquée, XLVIII(2) :85-98. | Numdam

[19] Ghattas B. ( 1999), Importance des variables dans les méthodes CART, Revue de modulad, 24 :29-39.

[20] Hastie T., Buja A. and Tibshirani R. ( 1995), Penalized discriminant analysis, Annals of Statistics, 23 :73-102. | MR 1331657 | Zbl 0821.62031

[21] Hastie T., Tibshirani R. and Friedman J.( 2001), The Elements of Statistical Learning, Springer. | MR 1851606 | Zbl 0973.62007

[22] Leurgans S., Moyeed R. and Silverman B. ( 1993), Canonical correlation analysis when the data are curves, Journal of the Royal Statistical Society Series B, 55 :725-740. | MR 1223939 | Zbl 0803.62049

[23] Mallat S. ( 1998), A wavelet tour of signal processing, Academic Press. | MR 1614527 | Zbl 0937.94001

[24] Misiti M., Misiti Y., Oppenheim G. and Poggi J.-M. ( 2003), Les ondelettes et leurs applications, Hermes.

[25] Ramsay J. and Silverman B. ( 1997), Functional Data Analysis, Springer. | MR 2168993 | Zbl 0882.62002

[26] Ramsay J. and Silverman B. ( 2002), Applied Functional Data Analysis, Springer. | MR 1910407 | Zbl 1011.62002

[27] Rossi F. and Conan-Guez B. ( 2005), Functional multi-layer perceptron : a non-linear tool for functional data analysis, Neural networks, 18(1) :45-60. | Zbl 1085.68134

[28] Sauvé M. andTuleau C. ( 2006), Variable selection through CART, Rapport de recherche, INRIA, 5912 :l-30.

[29] Vannucci M., Brown P.J. and Fearn T. ( 2003), A decision theoretical approach to wavelet regression on curves with a high number of regressors, Journal of Statistical planning and inference, 112 :195-212. | MR 1961730 | Zbl 1032.62004

[30] Vidakovic B. ( 1999), Statistical modeling by wavelets, Wiley. | MR 1681904 | Zbl 0924.62032