Non-parametric estimation in a semimartingale regression model. Part 1. Oracle inequalities
Vestnik Tomskogo gosudarstvennogo universiteta. Matematika i mehanika, no. 3 (2009), pp. 23-41 Cet article a éte moissonné depuis la source Math-Net.Ru

Voir la notice de l'article

This paper considers the problem of estimating a periodic function in a continuous time regression model with a general square integrable semimartingale noise. A model selection adaptive procedure is proposed. Sharp non-asymptotic oracle inequalities have been derived.
Keywords: Non-asymptotic estimation; Non-parametric regression; Model selection; Sharp oracle inequality; Semimartingale noise.
@article{VTGU_2009_3_a2,
     author = {V. V. Konev and S. M. Pergamenshchikov},
     title = {Non-parametric estimation in a~semimartingale regression model. {Part~1.} {Oracle} inequalities},
     journal = {Vestnik Tomskogo gosudarstvennogo universiteta. Matematika i mehanika},
     pages = {23--41},
     year = {2009},
     number = {3},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/VTGU_2009_3_a2/}
}
TY  - JOUR
AU  - V. V. Konev
AU  - S. M. Pergamenshchikov
TI  - Non-parametric estimation in a semimartingale regression model. Part 1. Oracle inequalities
JO  - Vestnik Tomskogo gosudarstvennogo universiteta. Matematika i mehanika
PY  - 2009
SP  - 23
EP  - 41
IS  - 3
UR  - http://geodesic.mathdoc.fr/item/VTGU_2009_3_a2/
LA  - ru
ID  - VTGU_2009_3_a2
ER  - 
%0 Journal Article
%A V. V. Konev
%A S. M. Pergamenshchikov
%T Non-parametric estimation in a semimartingale regression model. Part 1. Oracle inequalities
%J Vestnik Tomskogo gosudarstvennogo universiteta. Matematika i mehanika
%D 2009
%P 23-41
%N 3
%U http://geodesic.mathdoc.fr/item/VTGU_2009_3_a2/
%G ru
%F VTGU_2009_3_a2
V. V. Konev; S. M. Pergamenshchikov. Non-parametric estimation in a semimartingale regression model. Part 1. Oracle inequalities. Vestnik Tomskogo gosudarstvennogo universiteta. Matematika i mehanika, no. 3 (2009), pp. 23-41. http://geodesic.mathdoc.fr/item/VTGU_2009_3_a2/

[1] Akaike H., “A new look at the statistical model identification”, IEEE Trans. on Automatic Control, 1974, 716–723 | DOI | MR | Zbl

[2] Barron A., Birgé L., and Massart P., “Risk bounds for model selection via penalization”, Probab. Theory Relat. Fields, 113:3 (1999), 301–413 | DOI | MR | Zbl

[3] Cao Y. and Golubev Y., “On oracle inequaliies related to a polynomial fitting”, Math. Meth. Stat., 14:4 (2006), 431–450 | MR

[4] Cavalier L., Golubev G.K., Picard D. and Tsybakov A., “Oracle inequalities for inverse problems”, Ann. Statist., 30:3 (2002), 843–874 | DOI | MR | Zbl

[5] Fourdrinier D. and Pergamenshchikov S., “Improved selection model method for the regression with dependent noise”, Ann. Institute Statist. Math., 59:3 (2007), 435–464 | DOI | MR | Zbl

[6] Galtchouk L. and Pergamenshchikov S., “Nonparametric sequential estimation of the drift in diffusion processes via model selection”, Math. Meth. Stat., 13:1 (2004), 25–49 | MR | Zbl

[7] Galtchouk L. and Pergamenshchikov S., “Sharp non-asymptotic oracle inequalities for nonparametric heteroscedastic regression models”, J. Non-parametric Stat., 21:1 (2009), 1–18 | DOI | MR | Zbl

[8] Galtchouk L. and Pergamenshchikov S., “Adaptive asymptotically efficient estimation in heteroscedastic non-parametric regression”, J. Korean Statist. Soc., 38:4 (2009), 305–322 | DOI | MR | Zbl

[9] Galtchouk L. and Pergamenshchikov S., Adaptive asymptotically efficient estimation in heteroscedastic non-parametric regression via model selection, URL: , 2009 http://hal.archives-ouvertes.fr/hal-00326910/fr/ | MR

[10] Galtchouk L. and Pergamenshchikov S., Adaptive sequential estimation for ergodic diffusion processes in quadratic metric. Part 1. Sharp non-asymptotic oracle inequalities, Prépublication 2007/06, IRMA, Université Louis Pasteur de Strasbourg, 2007

[11] Galtchouk L. and Pergamenshchikov S., Adaptive sequential estimation for ergodic diffusion processes in quadratic metric. Part 2. Asymptotic efficiency, Prépublication 2007/07, IRMA, Université Louis Pasteur de Strasbourg, 2007

[12] Goldfeld S.M. and Quandt R.E., Nonlinear Methods in Econometrics, North-Holland, London, 1972 | MR | Zbl

[13] Kneip A., “Ordered linear smoothers”, Ann. Stat., 22:2 (1994), 835–866 | DOI | MR | Zbl

[14] Konev V.V. and Pergamenshchikov S.M., “General model selection estimation of a periodic regression with a Gaussian noise”, Ann. Institute Statist. Math., 2008 | DOI

[15] Jacod J. and Shiryaev A.N., Limit theorems for stochastic processes, v. 1, Springer, N.Y., 1987 | MR | Zbl

[16] Mallows C., “Some comments on $C_p$”, Technometrics, 15 (1973), 661–675 | DOI | Zbl

[17] Massart P., “A non-asymptotic theory for model selection”, ECM Stockholm, 2005, 309–323 | MR | Zbl

[18] Nussbaum M., “Spline smoothing in regression models and asymptotic efficiency in $L_2$”, Ann. Statist., 13:3 (1985), 984–997 | DOI | MR | Zbl

[19] Pinsker M.S., “Optimal filtration of square-integrable signals in Gaussian noise”, Probl. Inform. Transmis., 16:2 (1980), 120–133 | MR | Zbl