Электронная библиотека (репозиторий) Томского государственного университета
Beltaief, Slim | Pergamenshchikov, Serguei M.

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Add   Adaptive efficient estimation for generalized semi‑Markov big data models
Authors: Barbu, Vlad Stefan | Beltaief, Slim | Pergamenshchikov, Serguei M.
Source: Annals of the Institute of Statistical Mathematics. 2022. Vol. 74, № 5. P. 925-955
Type: статьи в журналах
Date: 2022
Description: In this paper we study generalized semi-Markov high dimension regression models in continuous time, observed at fixed discrete time moments. The generalized semi-Markov process has dependent jumps and ... More
Add   Adaptive robust efficient estimation methods in statistical models generated by fractal Poisson processes
Authors: Beltaief, Slim | Barbu, Vlad Stefan | Pergamenshchikov, Serguei M.
Source: Международная научная конференция "Робастная статистика и финансовая математика – 2020" (15-16 декабря 2020 г.) : сборник статей. Томск, 2021. С. 14-22
Type: статьи в сборниках
Date: 2021
Description: We study a non parametric estimation problem for regression models in continuous time with noises defined through non -Gaussian semi - Markov processes with jumps. Moreover, we assume that the jumps a ... More
Add   Model selection for the robust efficient signal processing observed with small Lévy noise
Authors: Beltaief, Slim | Chernoyarov, Oleg V. | Pergamenshchikov, Serguei M.
Source: Annals of the Institute of Statistical Mathematics. 2020. Vol. 72, № 5. P. 1205-1235
Type: статьи в журналах
Date: 2020
Description: We develop a new model selection method for an adaptive robust efficient nonparametric
Add   Robust adaptive efficient estimation for a semi-Markov continuous time regression from discrete data
Authors: Barbu, Vlad Stefan | Beltaief, Slim | Pergamenshchikov, Serguei M.
Source: Теория вероятностей и ее применения. 2019. Т. 64, № 1. С. 156-157
Type: статьи в журналах
Date: 2019
Description: In this article we consider the nonparametric robust estimation problem for regression models in continuous time with semi-Markov noises observed in discrete time moments. An adaptive model selection ... More
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