Super-efficient robust estimation in Lévy continuous time regression models from discrete data

In this paper we consider the nonparametric estimation problem for a continuous time regression model with non-Gaussian Lévy noise of small intensity. The estimation problem is studied under the condition that the observations are accessi-ble only at discrete time moments. In this paper, based on th...

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Bibliographic Details
Published in:Вестник Томского государственного университета. Математика и механика № 85. С. 22-31
Main Author: Nikiforov, Nikita I.
Other Authors: Pergamenshchikov, Serguei M., Pchelintsev, Evgeny A.
Format: Article
Language:English
Subjects:
Online Access:http://vital.lib.tsu.ru/vital/access/manager/Repository/koha:001009719
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245 1 0 |a Super-efficient robust estimation in Lévy continuous time regression models from discrete data  |c N. I. Nikiforov, S. M. Pergamenshchikov, E. A. Pchelintsev 
246 1 1 |a Суперэффективное робастное оценивание в непрерывных регрессионных моделях Леви по дискретным данным 
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520 3 |a In this paper we consider the nonparametric estimation problem for a continuous time regression model with non-Gaussian Lévy noise of small intensity. The estimation problem is studied under the condition that the observations are accessi-ble only at discrete time moments. In this paper, based on the nonparametric estimation method, a new estimation procedure is constructed, for which it is shown that the rate of convergence, up to a certain logarithmic coefficient, is equal to the parametric one, i.e., super-efficient property is provided. Moreover, in this case, the Pinsker constant for the Sobolev ellipse with the geometrically increasing coefficients is calculated, which turns out to be the same as for the case of complete observations. 
653 |a непараметрическое оценивание 
653 |a модели негауссовской регрессии в непрерывном времени 
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700 1 |a Pergamenshchikov, Serguei M. 
700 1 |a Pchelintsev, Evgeny A. 
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