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On MLE methods for dynamical systems with fractionally differenced noise spectra

Research output: Contribution to conference › Paper › peer-review

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On MLE methods for dynamical systems with fractionally differenced noise spectra. / Vivero, O.; Heath, W.P.
2010. 1842-1847 Paper presented at Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, Shanghai, China.

Research output: Contribution to conference › Paper › peer-review

HarvardHarvard

Vivero, O & Heath, WP 2010, 'On MLE methods for dynamical systems with fractionally differenced noise spectra', Paper presented at Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, Shanghai, China, 15/12/09 - 18/12/09 pp. 1842-1847. https://doi.org/10.1109/CDC.2009.5399549

APA

Vivero, O., & Heath, W. P. (2010). On MLE methods for dynamical systems with fractionally differenced noise spectra. 1842-1847. Paper presented at Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, Shanghai, China. https://doi.org/10.1109/CDC.2009.5399549

CBE

Vivero O, Heath WP. 2010. On MLE methods for dynamical systems with fractionally differenced noise spectra. Paper presented at Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, Shanghai, China. https://doi.org/10.1109/CDC.2009.5399549

MLA

Vivero, O. and W.P. Heath On MLE methods for dynamical systems with fractionally differenced noise spectra. Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, 15 Dec 2009, Shanghai, China, Paper, 2010. 6 p. https://doi.org/10.1109/CDC.2009.5399549

VancouverVancouver

Vivero O, Heath WP. On MLE methods for dynamical systems with fractionally differenced noise spectra. 2010. Paper presented at Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, Shanghai, China. doi: 10.1109/CDC.2009.5399549

Author

Vivero, O. ; Heath, W.P. / On MLE methods for dynamical systems with fractionally differenced noise spectra. Paper presented at Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, Shanghai, China.6 p.

RIS

TY - CONF

T1 - On MLE methods for dynamical systems with fractionally differenced noise spectra

AU - Vivero, O.

AU - Heath, W.P.

PY - 2010/1/29

Y1 - 2010/1/29

N2 - Maximum likelihood is an attractive estimator for linear systems with finite order. In the case of fractionally differenced processes, the maximum likelihood estimator becomes numerically intractable for large data sets. An algorithm for the estimation of the fractal dimension of a process that addresses the ill-conditioning of its covariance matrix is proposed. The algorithm reduces the variance of the fractal dimension estimate by segmenting the data into several sequences of relatively small length. The algorithm possesses better numerical properties than the ones proposed in the literature. An extension to the algorithm is proposed in order to cover ARFIMA models and its convergence properties are discussed. While no guarantee of its convergence is offered, the algorithm's good behaviour is shown in simulations.

AB - Maximum likelihood is an attractive estimator for linear systems with finite order. In the case of fractionally differenced processes, the maximum likelihood estimator becomes numerically intractable for large data sets. An algorithm for the estimation of the fractal dimension of a process that addresses the ill-conditioning of its covariance matrix is proposed. The algorithm reduces the variance of the fractal dimension estimate by segmenting the data into several sequences of relatively small length. The algorithm possesses better numerical properties than the ones proposed in the literature. An extension to the algorithm is proposed in order to cover ARFIMA models and its convergence properties are discussed. While no guarantee of its convergence is offered, the algorithm's good behaviour is shown in simulations.

U2 - 10.1109/CDC.2009.5399549

DO - 10.1109/CDC.2009.5399549

M3 - Papur

SP - 1842

EP - 1847

T2 - Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference

Y2 - 15 December 2009 through 18 December 2009

ER -