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15685 Improved variance estimation along sample eigenvectors
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Hendrikse, A.J. and Veldhuis, R.N.J. and Spreeuwers, L.J. (2009) Improved variance estimation along sample eigenvectors. In: Proceedings of the 30th Symposium on Information Theory in the Benelux, 28-29 May 2009, Eindhoven, The Netherlands. pp. 25-32. Werkgemeenschap voor Informatie- en Communicatietheorie. ISBN 978-90-386-1852-4

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Abstract

Second order statistics estimates in the form of sample eigenvalues and sample eigenvectors give a sub optimal description of the population density. So far only attempts have been made to reduce the bias in the sample eigenvalues.
However, because the sample eigenvectors differ from the population eigenvectors as well, the population eigenvalues are biased estimates of the variances along the sample eigenvectors. Therefore correction of the sample eigenvalues towards the population eigenvalues is not sufficient. The experiments in this paper show that
replacing the sample eigenvalues with the variances along the sample eigenvectors often results in better estimates of the population density than replacing the sample eigenvalues with the population eigenvalues.

Item Type:Conference or Workshop Paper (Full Paper, Talk)
Research Group:EWI-SAS: Signals and Systems
Research Program:CTIT-ISTRICE: Integrated Security and Privacy in a Networked World
Research Project:3D Face, TURBINE: TrUsted Revocable Biometric IdeNtitiEs
Uncontrolled Keywords:Density estimation, eigenvalue estimation, variance correction
ID Code:15685
Status:Published
Deposited On:02 March 2010
Refereed:No
International:No
More Information:statisticsmetis

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