Please use this identifier to cite or link to this item:
https://elib.bsu.by/handle/123456789/233394| Title: | Non-asymptotic confidence estimation of the autoregressive parameter in AR(1) process with an unknown noise variance |
| Authors: | Vorobeychikov, S. E. Burkatovskaya, Yu. B. |
| 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. 315-318. |
| Abstract: | The paper considers the problem of estimating the autoregressive parameter in the first-order autoregressive with Gaussian noises, when the noise variance is unknown. We propose the non-asymptotic technique for compensating the unknown variance, and then, for constructing an estimator. The results of Monte-Carlo simulations are given |
| URI: | http://elib.bsu.by/handle/123456789/233394 |
| ISBN: | 978-985-566-811-5 |
| Sponsorship: | This study was supported by The Ministry of Education and Science of the Russian Federation, Goszadanie No 2.3208.2017/4.6 |
| Appears in Collections: | 2019. Computer Data Analysis and Modeling : Stochastics and Data Science |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 315-318.pdf | 361,6 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.