Asymptotics of suprema of Gaussian fields with applications to kernel density estimators
Teoriâ veroâtnostej i ee primeneniâ, Tome 59 (2014) no. 3, pp. 499-541 Cet article a éte moissonné depuis la source Math-Net.Ru

Voir la notice de l'article

@article{TVP_2014_59_3_a4,
     author = {L. A. Sakhanenko},
     title = {Asymptotics of suprema of {Gaussian} fields with applications to kernel density estimators},
     journal = {Teori\^a vero\^atnostej i ee primeneni\^a},
     pages = {499--541},
     year = {2014},
     volume = {59},
     number = {3},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/TVP_2014_59_3_a4/}
}
TY  - JOUR
AU  - L. A. Sakhanenko
TI  - Asymptotics of suprema of Gaussian fields with applications to kernel density estimators
JO  - Teoriâ veroâtnostej i ee primeneniâ
PY  - 2014
SP  - 499
EP  - 541
VL  - 59
IS  - 3
UR  - http://geodesic.mathdoc.fr/item/TVP_2014_59_3_a4/
LA  - ru
ID  - TVP_2014_59_3_a4
ER  - 
%0 Journal Article
%A L. A. Sakhanenko
%T Asymptotics of suprema of Gaussian fields with applications to kernel density estimators
%J Teoriâ veroâtnostej i ee primeneniâ
%D 2014
%P 499-541
%V 59
%N 3
%U http://geodesic.mathdoc.fr/item/TVP_2014_59_3_a4/
%G ru
%F TVP_2014_59_3_a4
L. A. Sakhanenko. Asymptotics of suprema of Gaussian fields with applications to kernel density estimators. Teoriâ veroâtnostej i ee primeneniâ, Tome 59 (2014) no. 3, pp. 499-541. http://geodesic.mathdoc.fr/item/TVP_2014_59_3_a4/

[1] Bickel P. J., Rosenblatt M., “On some global measures of the deviations of density function estimates”, Ann. Statist., 1 (1973), 1071–1095 | DOI | MR | Zbl

[2] Gikhman I. I., Skorokhod A. V., Vvedenie v teoriyu sluchainykh protsessov, Nauka, M., 1965, 655 pp.

[3] Giné E., Koltchinskii V., Sakhanenko L., “Convergence in distribution of self-normalized sup-norms of kernel density estimators”, High Dimensional Probability III, eds. J. Hoffmann-Jörgensen et al., Birkhäuser, Basel, 2003, 241–253 | DOI | MR | Zbl

[4] Giné E., Koltchinskii V., Sakhanenko L., “Kernel density estimators: convergence in distribution for weighted sup-norms”, Probab. Theory Related Fields, 130:2 (2004), 167–198 | DOI | MR | Zbl

[5] Giné E., Koltchinskii V., Zinn J., “Weighted uniform consistency of kernel density estimators”, Ann. Probab., 32:3B (2004), 2570–2605 | MR | Zbl

[6] Komlós J., Major P., Tusnády G., “An approximation of partial sums of independent RV's and the sample DF, I”, Z. Wahrscheinlichtkeitstheor. verw. Geb., 32 (1975), 111–131 | DOI | MR | Zbl

[7] Konakov V. D., Piterbarg V. I., “On the convergence rate of maximal deviation distribution for kernel regression estimates”, J. Multivariate Anal., 15 (1984), 279–294 | DOI | MR | Zbl

[8] Ledoux M., Talagrand M., Probability on Banach Spaces, Springer-Verlag, New York, 1991, 480 pp. | Zbl

[9] Lifshits M. A., Gaussovskie sluchainye funktsii, TViMS, Kiev, 1995, 246 pp.

[10] Pickands J. III, “Upcrossing probabilities for stationary Gaussian processes”, Trans. Amer. Math. Soc., 145 (1969), 51–73 | DOI | MR | Zbl

[11] Piterbarg V., Asymptotic Methods in the Theory of Gaussian Processes and Fields, Transl. Math. Monogr., 148, Amer. Math. Soc., Providence, RI, 1996, 206 pp. | MR

[12] Rio E., “Local invariance principles and their application to density estimation”, Probab. Theory Related Fields, 98:1 (1994), 21–45 | DOI | MR | Zbl

[13] van der Vaart A., Wellner J. A., Weak Convergence and Empirical Processes with Applications to Statistics, Springer-Verlag, New York, 1996, 508 pp. | MR