Publication detail

Evaluation of methods for AR coefficients estimation using monte carlo analysis

KLEJMOVÁ, E.

Original Title

Evaluation of methods for AR coefficients estimation using monte carlo analysis

English Title

Evaluation of methods for AR coefficients estimation using monte carlo analysis

Type

conference paper

Language

en

Original Abstract

Aim of this paper is to give recommendation for work with methods used for estimation of coefficients of autoregressive process. We applied Monte Carlo simulations to investigate perfor-mance of Burg, Yule-Walker and covariance methods. Evaluation of precision of spectral estimation is done with focus on signal length and lag order. The results are presented in graphical form and briefly discussed. Taking these results into account, Yule-Walker method shows better performance in case of long length signals and in case of overvalued lag order. Burg and covariance methods provide better results in case of short length signal and undervalued lag order.

English abstract

Aim of this paper is to give recommendation for work with methods used for estimation of coefficients of autoregressive process. We applied Monte Carlo simulations to investigate perfor-mance of Burg, Yule-Walker and covariance methods. Evaluation of precision of spectral estimation is done with focus on signal length and lag order. The results are presented in graphical form and briefly discussed. Taking these results into account, Yule-Walker method shows better performance in case of long length signals and in case of overvalued lag order. Burg and covariance methods provide better results in case of short length signal and undervalued lag order.

Keywords

Autoregressive process, AIC, Burg method, Yule-Walker method, covariance method

Released

28.04.2016

Publisher

Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií

Location

Brno

ISBN

978-80-214-5350-0

Book

Proceedings of the 22nd Conference STUDENT EEICT 2016

Edition number

1

Pages from

375

Pages to

379

Pages count

5

BibTex


@inproceedings{BUT124486,
  author="Eva {Klejmová}",
  title="Evaluation of methods for AR coefficients estimation using monte carlo analysis",
  annote="Aim of this paper is to give recommendation for work with methods used for estimation of coefficients of autoregressive process. We applied Monte Carlo simulations to investigate perfor-mance of Burg, Yule-Walker and covariance methods. Evaluation of precision of spectral estimation is done with focus on signal length and lag order. The results are presented in graphical form and briefly discussed. Taking these results into account, Yule-Walker method shows better performance in case of long length signals and in case of overvalued lag order. Burg and covariance methods provide better results in case of short length signal and undervalued lag order.",
  address="Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií",
  booktitle="Proceedings of the 22nd Conference STUDENT EEICT 2016",
  chapter="124486",
  howpublished="electronic, physical medium",
  institution="Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií",
  year="2016",
  month="april",
  pages="375--379",
  publisher="Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií",
  type="conference paper"
}