Non-asymptotic confidence estimation of the autoregressive parameter in AR(1) process by noisy observations

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Non-asymptotic confidence estimation of the autoregressive parameter in AR(1) process by noisy observations	847 KB	Adobe Acrobat PDF	Read	Download
DOI Доступ к ресурсу на сайте издателя			10.17223/19988605/59/9

Title: Non-asymptotic confidence estimation of the autoregressive parameter in AR(1) process by noisy observations
Title: Доверительное неасимптотическое оценивание параметра авторегрессии AR(1) по зашумленным данным
Creator: Vorobeychikov, Sergey E.
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Pupkov, Andrey V.
Date: 2022
DOI: 10.17223/19988605/59/9
Description: For parameter in an AR(1) process corrupted by noise, the paper proposes the construction of confi-dence interval for unknown parameter with a prescribed coverage probability. The noises both in observable and in unobservable processes are assumed to be Gaussian with unknown variance. The estimation procedure is non-asymptotic and uses a special stopping rule. The results of numerical simulation by Monte-Carlo method are presented.