Abstract
The paper considers the estimation problem of the autoregressive parameter in the first-order autoregressive process with Gaussian noises when the noise variance is un-known. We propose a non-asymptotic technique to compensate the unknown variance, and then, to construct a point estimator with any prescribed mean square accuracy. Also a fixed-width confidence interval with any prescribed coverage accuracy is proposed. The results of Monte-Carlo simulations are given.
Original language | English |
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Pages (from-to) | 19-26 |
Number of pages | 8 |
Journal | Austrian Journal of Statistics |
Volume | 49 |
Issue number | 4 |
DOIs | |
Publication status | Published - 14 Apr 2020 |
Keywords
- Autoregressive process
- Confidence interval
- Non-asymptotic estimation
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty
- Applied Mathematics