Please use this identifier to cite or link to this item:
https://elib.bsu.by/handle/123456789/233385| Title: | Drift parameter estimation in Gaussian regression model by continuous and discrete observations |
| Authors: | Ralchenko, K. |
| Keywords: | ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Математика ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Кибернетика |
| Issue Date: | 2019 |
| Publisher: | Minsk : BSU |
| Citation: | Computer Data Analysis and Modeling: Stochastics and Data Science : Proc. of the Twelfth Intern. Conf., Minsk, Sept. 18-22, 2019. – Minsk : BSU, 2019. – P. 285-288. |
| Abstract: | The paper is devoted to the maximum likelihood estimation in the regression model of the form Xt = θG(t) + Bt, where B is a Gaussian process, G(t) is a known function, and θ is an unknown drift parameter. The estimation techniques for the cases of discrete-time and continuous-time observations are presented. As examples, models with fractional Brownian motion, sub-fractional Brownian motion and two independent fractional Brownian motions are considered |
| URI: | http://elib.bsu.by/handle/123456789/233385 |
| ISBN: | 978-985-566-811-5 |
| Appears in Collections: | 2019. Computer Data Analysis and Modeling : Stochastics and Data Science |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 285-288.pdf | 417,47 kB | Adobe PDF | View/Open |
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